Hubbry Logo
NovelAINovelAIMain
Open search
NovelAI
Community hub
NovelAI
logo
8 pages, 0 posts
0 subscribers
Be the first to start a discussion here.
Be the first to start a discussion here.
NovelAI
NovelAI
NovelAI
View on Wikipedia
from Wikipedia

NovelAI
DeveloperAnlatan[1]
Initial release2021
TypeText-generation model, text-to-image model
LicenseProprietary
Websitenovelai.net

NovelAI is an online cloud-based, SaaS model, and a paid subscription service for AI-assisted storywriting[2][3][4] and text-to-image synthesis,[5] originally launched in beta on June 15, 2021,[6] with the image generation feature being implemented later on October 3, 2022.[5][7] NovelAI is owned and operated by Anlatan, which is headquartered in Wilmington, Delaware.[1]

Features

[edit]
A screenshot of the main image generation page
An image generated by NovelAI based on the text prompt "Girl, impressionism, (faint light), looking at hand, business suit, Rectangular glasses"

NovelAI uses GPT-based large language models (LLMs)[8][9] to generate storywriting and prose.[10] It has several models, such as Calliope, Sigurd, Euterpe, Krake, and Genji, with Genji being a Japanese-language model.[11][12] The service also offers encrypted servers and customizable editors.[10][13]

For AI art generation, which generates images from text prompts, NovelAI uses a custom version of the source-available Stable Diffusion[2][14] text-to-image diffusion model called NovelAI Diffusion, which is trained on a Danbooru-based[5][1][15][16] dataset.

NovelAI is also capable of generating a new image based on an existing image.[17] The NovelAI terms of service states that all generated content belongs to the user, regardless if the user is an individual or a corporation.[5] Anlatan states that generated images are not stored locally on their servers.[1]

History

[edit]

On April 28, 2021, Anlatan officially launched NovelAI.[6][18]

On June 15, 2021, Anlatan released their finetuned GPT-Neo-2.7B model from EleutherAI named Calliope, after the Greek Muses. A day later, they released their Opus-exclusive GPT-J-6B finetuned model named Sigurd,[6][18] after the Norse/Germanic hero.

On March 21, 2023, Nvidia and CoreWeave announced Anlatan being one of the first CoreWeave customers to deploy NVIDIA's H100 Tensor Core GPUs[19] for new LLM model inferencing and training.[4][20][21]

On April 1, 2023, Anlatan added ControlNet features to their text-to-image NovelAI Diffusion model.[22][23]

On May 16, 2023, Anlatan announced that they named their H100 cluster Shoggy, a reference to H.P. Lovecraft's Shoggoths, which was used to pre-train an undisclosed 8192 token context LLM in-house model.[24]

Reception and controversy

[edit]
Art generated by NovelAI's furry diffusion model, depicting a dragon in a forest

Following the implementation of image generation, NovelAI became a widely-discussed topic in Japan, with some online commentators noting that its image synthesis features are very adept at producing close impressions of anime characters,[5] including lolicon and shotacon imagery,[25] while others have expressed concern that it is a paid service reliant on a diffusion model, while the original machine learning training data consists of images used without the consent of the original artists.[5][26][1][15][16] Attorney Kosuke Terauchi notes that, since a revision of the law in 2018, it is no longer illegal in Japan for machine learning models to scrape copyrighted content from the internet to use as training data;[1] meanwhile, in the United States where NovelAI is based, there is no specific legal framework which regulates machine learning, and thus the fair use doctrine of US copyright law applies instead.[1] Danbooru has posted an official statement in regards to NovelAI's use of the site's content for AI training, expressing that Danbooru is not affiliated with NovelAI, and does not endorse nor condone NovelAI's use of artists' artworks for machine learning.[1][15][14]

FayerWayer described NovelAI as a service capable of generating hentai.[27] Manga artist Izumi Ū commented that while the manga style art generated by NovelAI is highly accurate, there are still imperfections in the output, although he views these as human-like in a favourable light nonetheless.[28]

In response to the topic of NovelAI, Narugami, founder of the Japanese freelance artist commissioning website Skeb [ja], stated on October 5, 2022 that the use of AI image generation is prohibited on the platform since 2018.[29] Illustrations using NovelAI have been posted on social media and illustration posting sites, and by October 13, 2,111 works tagged with #NovelAI were posted on Pixiv. Pixiv has stated that it is not considering a complete elimination of creations that use AI,[30] though it requires AI-generated posts to be marked as such and allows users to filter them out.[31]

Incidents

[edit]

On October 6, 2022, NovelAI experienced a data breach where its software's source code was leaked.[32][33]

See also

[edit]

References

[edit]
[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

NovelAI

View on Grokipedia
from Grokipedia
NovelAI is a subscription-based platform launched in June 2021 by Anlatan, a Delaware-based , that provides tools for generative text and anime-style image creation. The platform employs proprietary large language models, such as the initial fine-tuned from GPT-Neo and later advancements like GLM-4.6, to assist users in crafting narratives with extended context lengths and multilingual support, alongside diffusion-based image models derived from with custom enhancements for higher fidelity and precision. NovelAI distinguishes itself through an uncensored content policy, enabling generation of unrestricted material including explicit themes, which emerged in response to in prior services like and has driven rapid user adoption, reaching over 40,000 subscribers within months of launch. Subscription tiers range from $10 to $25 monthly, offering unlimited generations and bonus credits, with ongoing model updates like Diffusion V4.5 emphasizing improved image quality and dataset extensions.

Overview

Founding and Core Mission

NovelAI was established in 2021 by Anlatan, a distributed of AI researchers and developers led by CEO and Head of Eren . The service initiated its open beta on June 16, 2021, initially focusing on AI-assisted storytelling through finetuned large language models derived from open-source architectures like GPT-Neo. This launch marked the transition from prototype development to a subscription-based platform, enabling users to generate narrative content with extended context lengths and customizable modules. The core mission of NovelAI centers on delivering uncensored generative AI tools for creative authorship, particularly in and anime-inspired synthesis, while prioritizing user privacy and control. Unlike platforms with content filters that restrict outputs based on ethical or regulatory guidelines, NovelAI commits to minimal intervention, allowing generations without predefined moral alignments or . This approach stems from the founders' emphasis on fostering unrestricted , supported by local for prompts and no retention of . Anlatan's vision underscores a dedication to high-quality, specialized models trained on literature and visual art datasets, aiming to empower users in crafting personalized narratives and visuals. The service's subscription model—ranging from $10 to $25 monthly—reflects a business oriented toward sustainable development of advanced, user-owned outputs, free from corporate data harvesting practices common in larger AI providers. This mission has positioned NovelAI as a niche leader in privacy-focused, freedom-oriented AI creativity.

Service Model and Accessibility

NovelAI employs a subscription-based service model with three primary tiers: Tablet at $10 USD per month, at $15 USD per month, and Opus at $25 USD per month. Each tier grants unlimited text generations using the platform's large models, alongside image capabilities differentiated by factors such as maximum resolution (up to 1024x1024 pixels), steps (up to 28), priority queuing during peak times, and monthly allotments of Anlas—the internal used for additional outputs or enhancements beyond base limits. Higher tiers like Opus include 10,000 bonus Anlas monthly, compared to 1,000 for lower tiers, enabling more extensive usage without supplemental purchases. Subscriptions are billed monthly in USD, with a 20% discount on Anlas top-ups, and users can opt for pay-as-you-go Anlas purchases for sporadic needs. A limited free trial provides 30 text or generations upon account creation, but lacks ongoing free access to core features. The platform emphasizes user privacy by processing generations on cloud servers without retaining user data or generated content, aligning with its design for unrestricted creative outputs including adult-themed material, in contrast to more censored competitors. Payments are handled via standard methods such as credit cards, though specifics like regional payment processors are managed through the user dashboard. Accessibility is facilitated through a web-based interface compatible with modern browsers including Chrome, , , and Edge, requiring no software installation on desktops or laptops. On mobile devices, the service supports access via mobile web browsers, with the option to install it as a (PWA) for an app-like experience, including home screen shortcuts and offline caching of static elements. No native mobile or desktop applications exist, prioritizing broad device compatibility over platform-specific optimizations; minimum requirements include JavaScript enablement and stable internet for API calls. The service is globally available without stated geographic restrictions, though users in certain regions may encounter payment or language interface variations, with multi-language support including Japanese via user settings. Interface customizations, such as theme adjustments and experimental editors, further enhance usability across devices.

Technical Foundation

Text Generation Models and Training

NovelAI's text generation capabilities are powered by a progression of large models, initially fine-tuned from open-source architectures and later incorporating continued pre-training or developments on curated datasets focused on . The company's models emphasize coherent , stylistic adaptability, and reduced content restrictions compared to heavily aligned commercial alternatives, achieved through selective data curation that prioritizes literary quality over broad web-scraped corpora. Core model training excludes user-submitted content to maintain , relying instead on a team-curated selection of pre-existing texts from diverse sources, cleaned for relevance to . Early models derived from EleutherAI's open releases, such as and , underwent fine-tuning to enhance fiction-specific outputs like plot continuity and character development. Subsequent iterations scaled parameters and context windows while refining objectives for longer-form generation. By 2023, models like incorporated extensive token-level —1.6 trillion tokens for both and the smaller —enabling robust handling of complex narratives. Newer releases, including Erato's continuation on the Llama 3 70B base using the Nerdstash dataset, and the massive GLM-4.6 (a 355 billion parameter architecture), support expanded multilingual capabilities (English, Japanese, Chinese) and context up to 36,864 tokens via rollover mechanisms.
Model NameBase ArchitectureParametersContext SizeRelease Date
(retired)GPT-Neo2.7BN/AJuly 16, 2021
6B2,048 tokensJune 16, 2021
Fairseq13B2,048 tokensJanuary 9, 2022
KrakeNeo-X20B2,048 tokensMarch 11, 2022
3B8,192 tokensMay 23, 2023
13B8,192 tokensJuly 28, 2023
EratoLlama 370BN/ASeptember 23, 2024
GLM-4.6355B28,672 + 8,192 rollover tokensSeptember 25, 2025 (updated October 1, 2025)
Training processes involve initial adaptation of base models via supervised fine-tuning on high-quality fiction corpora, followed by or iterative refinements to minimize repetition and hallucinations in story contexts. Users can further customize outputs through optional AI modules, trained separately on personal datasets (up to specified limits) to generation toward specific styles or lore without altering core models. This modular approach allows fine-grained control, such as genre-specific adaptations, while core models retain broad applicability for unfiltered creative tasks.

Image Generation Models and Enhancements

NovelAI's image generation relies on proprietary diffusion models developed in-house, initially derived from adaptations of Stable Diffusion but evolving to fully original architectures starting with V4. The service launched image generation in October 2022 with NovelAI Diffusion Anime V1, a fine-tuned variant optimized for anime-style outputs using a re-architected Stable Diffusion V1.4 base. Subsequent iterations improved fidelity, resolution, and prompt adherence, with V3 released on November 15, 2023, supporting higher base resolutions of 832x1216 pixels and reduced prompt guidance values for more natural results. By late 2024, NovelAI introduced V4 Curated on December 20, incorporating advancements like multi-character prompting, action tags for dynamic scenes, enhanced natural language understanding, support for longer prompts, and a 16-channel VAE for better color and detail rendering. The full V4 model followed on February 28, 2025, emphasizing higher precision and quality. V4.5, released in stages with Curated on May 5, 2025, and Full on May 29, 2025, further extended the training dataset for superior fidelity and versatility, available across subscription tiers. Specialized variants include Furry V3, launched April 22, 2024, tailored for anthropomorphic content with comparable resolution and sampler access. Models like V4.5 Full represent entirely original training from scratch, prioritizing anime aesthetics while enabling diverse styles through user controls. Key enhancements augment core with post-processing and tools. Vibe Transfer allows users to upload an reference to infuse stylistic elements into new outputs, guiding composition and without strict replication. supports targeted modifications via brush or rectangular selection tools, enabling precise edits to specific regions while preserving the rest of the . The Enhance feature applies iterative refinements, optionally increasing resolution during denoising for sharper results. Upscaling and further extend capabilities, with parameters like adjustable steps, Euler Ancestral sampler, and guidance noise optimizing quality and adherence to prompts, including quality tags and undesired content presets. Character references and base options facilitate consistent multi-element scenes, distinguishing NovelAI's toolkit for iterative, user-directed synthesis.

Customization and Fine-Tuning Mechanisms

NovelAI's language models, such as , , and subsequent iterations like Krake, are developed through proprietary fine-tuning processes applied to base architectures, using curated datasets to prioritize narrative coherence, stylistic variety, and reduced hallucinations in storytelling contexts. These fine-tunes enable differentiation by genre proficiency, with models like Genji optimized for Japanese text generation via targeted dataset refinement. Users previously accessed fine-tuning mechanisms via AI Modules, lightweight adapters that adjusted model behavior toward user-specified styles, themes, or reference materials without altering core weights. Introduced on , 2021, custom module training required Opus-tier subscription, uploading cleaned plain-text files (up to 10 MB, formatted as one paragraph per line without empty lines or special characters), selecting training steps (default 1000, processing at approximately 5 steps per second), and incurring Anlas costs queued for execution. Modules could be named, described, downloaded, shared, or imported across accounts, with Opus users allocated 8000 steps monthly. As of the latest documentation, training new custom AI Modules is no longer supported, rendering the feature legacy and restricting its use to older compatible models like and . Existing modules remain selectable in the story settings sidebar for influencing generation focus, categorized in galleries by type (e.g., style, theme), though compatibility is not guaranteed with newer models or future updates. Users can further customize text generation through structured prompting in the Memory field using the ATTG format [ Author: ; Title: ; Tags: ; Genre: ], which initializes story style and themes. Tags capitalize proper nouns only, with others lowercase, and are recommended to be limited to 3-5 key elements; genres use standard names such as fantasy or adventure. The Author and Title fields are optional to conserve context tokens. For image generation, NovelAI employs internally fine-tuned models derived from , incorporating modifications to architecture, training procedures, and datasets for enhanced fidelity in anime-inspired outputs, as seen in releases like NovelAI Diffusion V4 (February 2025) with expanded character prompting up to six distinct subjects. User customization relies on prompt-based controls, including tag strength, noise ratios, guidance scales, and tools such as , image-to-image, and Vibe Transfer for style , rather than direct fine-tuning of model parameters. No user-accessible fine-tuning for models exists, with official statements confirming no plans for custom image modules.

Core Features

Storywriting and Interactive Tools

NovelAI's storywriting tools center on an interactive that enables users to generate narrative continuations using proprietary large language models specially trained for smooth narrative generation, such as the current and models. Users initiate stories by providing prompts, after which the AI produces subsequent text segments based on configurable parameters like generation length, randomness, and repetition penalties. The platform supports two primary modes: Storyteller, which facilitates collaborative prose writing where the AI extends user-written passages in a linear narrative style, and Text Adventure, designed for branching, command-driven akin to classic text-based games. Key customization mechanisms include the Lorebook, a dynamic repository where users define entries containing character descriptions, world-building details, or plot elements that automatically insert into the AI's context when activation keys—such as names or keywords—appear in the text. Entries can incorporate explicit elements like fetishes and taboos for extreme R18 narratives, with triggers configurable for exact or fuzzy matching, insertion positions, priorities, and probabilities; this is particularly suited to Chinese novels, where the platform supports Chinese input and output, enabling consistent generation of themes such as hypnosis or NTR when combined with Memory and Author's Note fields. Users must comply with service terms to avoid prohibited content. This tool enhances consistency in long-form stories by maintaining persistent information without overwhelming the fixed context window. Additionally, Memory and Author's Note fields allow users to embed overarching story directives or stylistic guidelines at the prompt's forefront, influencing the AI's output globally to maintain style consistency; for example, users may employ the ATTG format in Memory, such as "[Author: A skilled fantasy novelist; Title: Traversing Sword and Magic; Tags: traversal, magic, adventure, romance, battle; Genre: fantasy, otherworld] followed by a story summary like 'Story so far: In a magic-filled medieval continent, the protagonist unexpectedly traverses, aiming to survive and find a way home.'", to set stylistic guidelines. These tools support simultaneous image generation, especially in anime style, for immersive visualization of narrative elements. User reviews note capabilities in generating coherent NSFW narratives, including erotic scenes and long-form erotica, through these consistency-maintaining features. Modules serve as specialized fine-tuning layers, with over 60 legacy options for older models adapting the AI to genres, themes, or authorial styles, and advanced experimental modules exclusive to newer models like and for effects such as descriptive enrichment or thematic emphasis. The Writer's Toolbox provides post-generation editing utilities, including retry functions to regenerate unsatisfactory outputs and manipulation tools for refining AI behavior. Advanced users access the Context Viewer to inspect token-level composition and probability distributions, aiding in and optimization of prompts. These features collectively enable iterative, user-guided , with export options preserving settings, lore, and history in formats like .story files for sharing or resumption.

Image Synthesis Capabilities

NovelAI's image synthesis employs diffusion-based generative models that iteratively refine random noise into coherent images guided by textual prompts, enabling users to produce high-fidelity visuals from descriptive inputs. The system supports text-to-image generation, image-to-image transformations, and editing tools such as canvas-based and outpainting, allowing iterative refinement of outputs. These capabilities originated from modifications to in 2022, incorporating architectural changes like hidden state utilization for better prompt adherence and aspect-ratio bucketing to handle varied compositions without distortion. The platform offers six selectable models tailored to specific aesthetics, including Anime and Furry variants optimized for anime and illustration fans, providing high-quality, natural depictions of characters and fantasy elements. For example, common prompts such as "アニメ風の女の子 紫髪 ショートヘア 競泳用水着 着用 立ち姿 かわいい" (a cute anime-style girl with purple short hair wearing a competitive swimsuit in a standing pose) generate illustrations popular on platforms like Pixiv, often created using NovelAI. with base resolutions up to 832x1216 pixels in later versions for enhanced detail and features enabling faster processing. NovelAI Diffusion Anime V3, released November 15, 2023, improved upon SDXL foundations through training adjustments like zero terminal SNR scaling, which stabilizes denoising at low signal-to-noise ratios, and aspect-ratio bucketing, yielding more anatomically consistent and stylistically precise anime-inspired outputs at reduced guidance strengths (typically 4-7). A companion Furry V3 model, launched April 22, 2024, extends these features to anthropomorphic subjects, supporting equivalent samplers, tag ordering, and vibe transfer for dynamic style adaptation. Advancements continued with the V4 Curated Preview on December 20, 2024, introducing multi-character prompting for distinct entity descriptions within a single scene, action tags for dynamic poses, extended prompt lengths, and a 16-channel VAE for finer representation, alongside that reduces reliance on rigid Danbooru-style tags. The full NovelAI Diffusion V4, deployed February 28, 2025, refines these for superior precision and quality, including year-specific style emulation (e.g., "year 2024" for contemporary ) and batch generation limits expanded to higher volumes. These models prioritize user control via parameters like steps (20-50 for balance), samplers (e.g., Euler a for speed), and strength settings for img2img modes, with guidance on art style tags for prompting unique artstyles available in the official tutorial covering tags, combinations, and usage tips. NovelAI's prompting system employs tag-based inputs similar to Danbooru, combining natural language with specific tags for characters (e.g., 1girl, 1boy, hair color, eye color, body type), poses (e.g., cowboy shot, full body, head tilt, from above), scenarios (e.g., starry background, gradient background, scenery), and other elements; artist styles can be invoked using artist names as tags. The official site provides prompt examples demonstrating this structure, while Danbooru serves as the primary reference for comprehensive tag lists due to training data similarities. Community resources on Reddit's r/NovelAi and rentry.co compile useful tags, poses, artists, and scenarios. This facilitates outputs in diverse genres from impressionistic scenes to detailed fantasy illustrations without imposed content restrictions. Such capabilities enable rapid prototyping of visual narratives, with real-time previews and Vibe Transfer for propagating stylistic elements across generations, distinguishing NovelAI from more censored alternatives by accommodating explicit or niche prompts aligned with user intent. Technical reports confirm these enhancements stem from proprietary training on curated datasets, yielding outputs that outperform base in fidelity for targeted domains like while maintaining computational efficiency for subscription-tier access.

Integration and User Controls

NovelAI's web-based interface offers comprehensive user controls for directing text and image outputs, emphasizing customization to align generations with user intent. For text generation, controls include adjustable context limits up to 8192 , sampling parameters like and top-p via config presets, and contextual elements such as , Author's Note, and Lorebook entries that persist across sessions to influence narrative continuity. Advanced options enable phrase biasing to favor or penalize specific , banned token lists to suppress undesired content, and real-time viewing of token probabilities in the Editor V2 for fine-grained analysis of AI decisions. Hotkeys facilitate efficient , such as Ctrl+Enter for AI generation requests and Alt+W to toggle sidebars. In image synthesis, users manipulate prompts, negative prompts, generation steps (typically 28-50), guidance scale (7-12 for adherence), and strength sliders for variations or enhancements. Control Tools support image-to-image workflows by uploading reference images as bases for pose, composition, or style guidance, with options to deviate via prompt adjustments or use as color maps, though incompatible with full model fine-tunes like V3. Director Tools provide post-generation edits including background removal, line art extraction, sketch conversion, colorization, emotion enhancement, and decluttering for refined outputs. The Edit Image Canvas allows inpainting, outpainting, and masking for targeted modifications. Integration between modalities enables seamless incorporation of generated images into text stories via uploads or descriptions in Lorebooks, fostering multimodal storytelling without external APIs. Interface settings permit personalization of readability (e.g., font size, line spacing), gesture controls for touch devices, and toggles for features like text streaming or experimental HypeBot commentary. Stories export fully, including settings, redo trees, and assets, supporting user sharing while maintaining privacy through local processing of sensitive data. As of 2025, features like Character Reference allow uploading images for consistent character rendering across generations, enhancing control over series continuity.

Development History

Inception and Initial Launch (2021)

The NovelAI project originated in late April 2021, when the Anlatan development team began building an AI platform focused on uncensored assistance, addressing limitations in existing models that enforced content filters. A closed alpha test followed shortly after , concluding around May 27, 2021, with roughly 100 participants generating 40,005 actions and processing 2 million tokens to refine the system's performance and gather feedback on core mechanics like text generation and . The service's initial public release took place on , 2021, as a paid subscription model utilizing fine-tuned open-source large language models, such as variants of GPT-Neo, to enable interactive narrative creation without ideological or thematic . emphasized privacy through encrypted user data, customization via tools like lore books for character and world-building, and tiered plans—Tablet (1,024-token context, 4,000 actions/month), Scroll (2,048-token context, 4,000 actions/month), and Opus (priority access)—to manage computational demands via a system. Post-launch scaling involved collaboration with GPU cloud provider CoreWeave, enabling rapid infrastructure expansion that supported growth to 40,000 subscribers within three months, driven by demand for unrestricted AI creativity tools.

Expansion to Multimodal Capabilities (2022)

In October 2022, NovelAI introduced image generation capabilities through its proprietary NovelAI Diffusion Anime model, marking a significant expansion from text-only to multimodal . The feature launched on October 3, 2022, enabling users to produce anime-style images directly from textual prompts, including descriptive tags and derived from ongoing narratives. This addition allowed subscribers to visualize characters, scenes, and concepts generated by the service's language models, such as , without imposed content restrictions, prioritizing unfiltered creative output. The NovelAI Diffusion Anime offered two variants: a curated model for consistent baseline quality and a full model for broader stylistic variety, both trained on datasets emphasizing anime aesthetics with specific tagging for reliable results. Key enhancements included an expanded CLIP token context of 231 tokens—up from the standard 77—to handle more detailed prompts, support for arbitrary aspect ratios to avoid cropping, and image-to-image functionalities like uploading references for edits, variations, or enhancements. Users could steer generations using emphasis syntax (e.g., curly braces for strengthening elements, square brackets for weakening) and an "Undesired Content" field to exclude specific features, with Opus-tier subscribers gaining unlimited generations at resolutions up to 640x640 pixels. A beta version, NovelAI Diffusion Furry, catered to anthropomorphic content, further diversifying multimodal applications. This multimodal integration bridged text and visual generation, permitting seamless incorporation of AI-produced images into story workflows—for instance, extracting character descriptors like "auburn , green eyes, skinny, tall" from text outputs to inform image prompts. By forgoing common in competing tools, NovelAI positioned itself as a tool for unrestricted artistic exploration, though generation costs scaled with resolution, steps, and batch size across subscription tiers. Initial updates post-launch, such as on October 21, 2022, refined configurations like classifier-free guidance for improved prompt adherence.

Iterative Improvements and Model Releases (2023–2025)

In 2023, NovelAI released on May 23, a 3 billion parameter model trained from scratch, featuring an 8,192-token context window and support for text adventures, instruction-following, and prose augmentation through specialized modules. This was followed by on July 28, a more advanced 13 billion parameter model also trained from scratch, emphasizing high-quality , text adventures, and generation within the same 8,192-token context limit. For image generation, the V2 model launched on October 20, introducing an "Undesired Content Strength" setting to enhance control over outputs using additional compute. Advancements continued into 2024 with the release of on September 23, based on the Llama 3 70B base model and fine-tuned on NovelAI's high-quality , offering an 8,192-token context and superior performance in long-form storytelling and adherence to prompts compared to prior models. In December, the Diffusion V4 Curated Preview debuted, incorporating year-specific style tags (e.g., "year 2024") to align generations with contemporary artistic trends and improving overall fidelity. This preview received an accuracy update on January 2, 2025. The year 2025 saw further text model iterations, including GLM-4.5 released as an untuned preview on September 26 exclusively for Opus subscribers, serving as a base for future fine-tunes with a 28,000-token context size. This evolved into GLM-4.6 by October 2, enhancing writing and role-playing capabilities, and expanded to all subscription tiers on October 15; the 355 billion parameter model supports a 28,672-token context plus 8,192-token rollover for extended sessions and includes multilingual features. On the image side, V4 Full launched February 28 with heightened precision and quality. V4.5 Full followed on May 29, leveraging an updated and expanded dataset for superior image quality and fidelity over V4. Additionally, weights for the second-generation V2 model were publicly released on July 8 to support research and non-commercial use. These releases reflect ongoing refinements in dataset curation, architectural tweaks, and context handling to prioritize user-driven creative outputs.

Reception and Impact

Achievements in AI Accessibility and Quality

NovelAI has advanced AI accessibility by offering a cloud-based subscription service that eliminates the need for users to possess high-end hardware or expertise in model , enabling individuals worldwide to generate text and images via a . Launched in with tiered plans starting at $10 per month, the platform provides unlimited text generations and bonus credits for image synthesis, alongside a free trial offering 30 image generations, thus lowering barriers for hobbyists and creators compared to resource-intensive alternatives like local setups. This model democratizes access to fine-tuned large language and diffusion models, particularly for niche creative applications such as anime-inspired art and unrestricted storytelling, where proprietary services often impose content filters. In terms of quality, NovelAI's iterative model releases have delivered competitive performance in creative generation tasks. The Diffusion V4.5 model, updated in updates emphasizing enhanced fidelity and detail over prior versions, supports resolutions up to 1024x1024 with 28-step sampling for high-fidelity anime-style outputs, as evidenced by user workflows achieving professional-grade results through and tools like Vibe Transfer. For text, the GLM-4.6 model, released on October 15, 2025, features a context window expanded to approximately 144,000 characters for premium tiers and improved multi-language coherence, outperforming predecessors in maintaining narrative consistency during long-form story generation. Independent reviews confirm superior narrative quality and rendering in specialized domains, with NovelAI edging out generalist tools in uncensored creative fidelity due to targeted fine-tuning on diverse datasets. These advancements stem from NovelAI's focus on user-driven customization, such as adjustable consistency sliders and undesired content filters, which enhance output precision without compromising accessibility. By prioritizing privacy—no data training on user inputs—and resisting broad , the platform has empowered thousands of daily users to produce original content, fostering a community of AI-assisted artists and writers. This approach contrasts with more restricted enterprise models, substantiating claims of elevated quality through empirical user satisfaction and iterative benchmarks in creative metrics rather than generic leaderboards.

User Base Growth and Community Engagement

NovelAI demonstrated rapid initial growth, scaling from zero to 40,000 users within three months of its launch, facilitated by high-performance GPU infrastructure that enabled handling increased demand for AI-assisted and image generation. By October 28, 2023, the service announced a milestone of 2.5 million total users, attributing the expansion to iterative model improvements and a focus on user and content freedom. This growth trajectory continued into subsequent years, with traffic rankings stabilizing around the global top 7,000 by September 2025, indicating persistent user interest amid competitive AI tools. Community engagement centers on dedicated platforms where users collaborate on and provide feedback. The official subreddit r/NovelAi maintains approximately 41,000 subscribers, serving as a hub for discussions on feature updates, troubleshooting, and sharing AI-generated stories and images. Similarly, the NovelAI server hosts over 51,000 members, fostering real-time interactions, including contributions to model fine-tuning datasets submitted via designated threads. These platforms have sustained activity through official announcements and user-driven initiatives, such as teasers for new models, despite occasional technical disruptions like a 2023 prune that inadvertently removed members. remains driven by the service's emphasis on uncensored outputs, attracting creators focused on niche genres like anime-style art and interactive narratives.

Broader Influence on AI Creativity Tools

NovelAI's resistance to content has contributed to a broader shift toward uncensored generative AI platforms, demonstrating commercial viability for tools prioritizing user freedom in creative outputs, particularly in niche domains like anime-inspired and . The unauthorized leak of NovelAI's fine-tuned on October 6, 2022, significantly impacted the open-source AI art ecosystem by disseminating high-quality anime-style generation capabilities derived from , enabling community derivatives such as Anything V3 that enhanced accessibility for independent developers and hobbyists. NovelAI's modifications to Stable Diffusion's architecture and training processes, implemented in 2022, improved generation quality and prompt adherence, particularly for stylized outputs, influencing subsequent fine-tuning practices in both and open-source tools aimed at specialized artistic domains. In AI-assisted storytelling, NovelAI's introduction of customizable modules and lorebooks—allowing users to train models on personal datasets for consistent narrative elements—has set a precedent for enhanced user agency, contrasting with more rigid systems and prompting competitors to incorporate similar personalization features for sustained engagement in long-form . By sustaining a subscription model focused on multimodal integration (text-to-image alongside generation), NovelAI has underscored the demand for cohesive suites, indirectly pressuring generalist tools to expand into visual aids or niche fine-tunes to retain users in competitive markets as of 2025.

Controversies and Criticisms

Model Leaks and Issues

On October 6, 2022, NovelAI experienced a security breach involving unauthorized access to its repositories and secondary storage, resulting in the leak of , , and model weights for its image generation system. The compromised materials primarily included fine-tuned versions of optimized for high-quality anime-style image generation, which represented substantial proprietary development efforts by NovelAI. NovelAI confirmed the incident publicly the following day, stating that the leak contained sensitive internal components but did not detail the extent of or immediate operational impacts. The leaked models quickly proliferated within the open-source AI community, where they were integrated into tools like the Automatic1111 web UI and used as foundational weights for derivative models such as Anything V3.0. This unauthorized distribution and adaptation effectively bypassed NovelAI's subscription-based access model, enabling free local inference of outputs comparable to the paid service at the time. Community forums documented rapid adoption, with users sharing prompts, VAE files, and emulation guides despite the models' proprietary status. The event marked one of the earliest major incidents of proprietary AI model theft in the ecosystem, underscoring the challenges of securing large weights against determined actors. Intellectually, the breach constituted a direct violation of NovelAI's copyrights and trade secrets, as the models embodied curated datasets, methodologies, and architectural modifications not publicly disclosed. Discussions in developer communities raised questions about the legal and ethical implications of downloading or fine-tuning leaked weights, with some arguing minimal risk of enforcement due to the diffuse nature of open-source distribution, though such use remained infringing under standard IP frameworks. No lawsuits or actions from NovelAI against leakers, hosts, or end-users were reported, potentially reflecting resource constraints or a focus on service continuity over litigation. The incident highlighted broader vulnerabilities in AI firms' IP protection, where model weights—often gigabytes in size—can be exfiltrated via exploits and shared anonymously on platforms like or mirrors. In August 2024, NovelAI released the weights of its earlier NovelAI V1 models under a permitting research, personal use, and historical preservation, explicitly excluding commercial applications or further redistribution. This move, occurring nearly two years post-leak, provided an official, sanctioned alternative to the pirated versions while preserving incentives for ongoing development of successor models like V4 and V4.5. The release did not retroactively legitimize prior unauthorized uses but aligned with trends in AI where partial open-sourcing mitigates competitive disadvantages from leaks. No evidence emerged of related IP disputes involving NovelAI's training data sources, though the company's emphasis on user-generated and licensed content for fine-tuning aimed to differentiate it from models trained on broadly scraped web corpora prone to challenges.

Debates Over NSFW Content and Censorship Resistance

NovelAI's emergence was precipitated by discontent with AI Dungeon's implementation of stringent content filters on April 28, 2021, which aimed to prevent the generation of illegal material—particularly involving minors—but resulted in widespread user complaints about invasive monitoring, false positives, and curtailed narrative freedom. In response, Anlatan launched NovelAI in June 2021 as a subscription-based service prioritizing uncensored large language models for text generation and, later, diffusion models for images, explicitly allowing NSFW outputs like and explicit artwork so long as they avoid prohibited illegal content such as material. This resistance to built-in alignment or moral guardrails has positioned NovelAI as a counterpoint to censored platforms like those powered by , where prompts involving adult themes are routinely rejected. Supporters within the AI community and NovelAI's user base contend that such policies enable authentic creative expression, especially in niche domains like and stylized art, without the paternalistic overreach that treats adult users as incapable of self-regulation. The service provides optional user-defined "undesired content" tags to steer generations away from specific elements, but refrains from service-wide filtering, a commitment reiterated in model updates through 2024. Critics, however, invoke ethical hazards, drawing parallels to uncensored fine-tunes of —which NovelAI has incorporated for image features—citing potential for non-consensual and amplified harms like or , as explored in a 2022 TechCrunch analysis of similar open models' rapid adoption on forums like for celebrity nudes. Experts quoted therein, such as AI ethicists Ravit Dotan and Abhishek Gupta, argue for proactive controls to mitigate "worst-case scenarios," though NovelAI's focus on non-photorealistic outputs limits direct applicability of deepfake risks compared to hyper-realistic generators. No verified reports link NovelAI specifically to widespread , but the platform's permissive approach underscores broader AI debates on whether empirical risks justify preemptively constraining tools that, in principle, mirror human artistic capabilities long predating digital generation.

Ethical and Regulatory Challenges

NovelAI's policy of minimal , particularly its allowance of NSFW material without algorithmic censorship, has elicited ethical concerns over potential misuse for generating exploitative or non-consensual depictions, even in stylized formats. Unlike platforms enforcing strict filters, NovelAI shifts responsibility to users, prohibiting illegal outputs such as child exploitation material while relying on user-reported bans and backend safeguards to prevent overt violations. This approach, rooted in prioritizing creative , draws criticism from those advocating proactive safeguards against harms like psychological dependency on AI companions or the normalization of fringe fantasies, though of widespread abuse remains anecdotal and unquantified in peer-reviewed studies. Regulatory challenges stem primarily from compliance with data protection laws and emerging AI frameworks, as NovelAI operates under U.S. jurisdiction ( law) while serving global users and adhering to GDPR for European data handling through encrypted processing and no-prompt-logging policies. The service mandates user age verification (18+) and lawful use, disclaiming liability for infringing generations while encrypting server data and enabling exports. However, as a provider of general-purpose generative models, it faces prospective scrutiny under regulations like the EU AI Act (effective 2024), which imposes transparency obligations, risk assessments, and potential high-risk classifications for unfiltered text-to-image systems capable of systemic harms, though NovelAI has not publicly disclosed specific compliance measures beyond general legal adherence. Critics, often from institutions favoring precautionary governance, argue that such resistance to built-in ethical alignments exacerbates gaps in decentralized misuse scenarios, yet NovelAI's empirically avoids the biases introduced by heavy-handed filters seen in competitors, fostering user-driven customization over top-down moral impositions. No major enforcement actions against NovelAI have been documented as of 2025, but ongoing global pushes for mandatory watermarking of AI outputs and liability for downstream harms could necessitate adaptations, balancing innovation with verifiable risk mitigation.

References

  1. https://blog.novelai.net/the-first-month-of-novelai-30a4a551a4ba
  2. https://www.reddit.com/r/NovelAi/comments/15nne4b/we_are_anlatan_the_team_behind_novelainet/
  3. https://novelai.medium.com/text-model-release-glm-4-6-for-all-tiers-efc0a5445973
  4. https://blog.novelai.net/novelai-improvements-on-stable-diffusion-e10d38db82ac
  5. https://news.ycombinator.com/item?id=29830792
  6. https://www.coreweave.com/blog/how-coreweave-helped-novelai-grow-from-0-to-40k-users-in-3-months
  7. https://novelai.net/
  8. https://novelai.net/updates
  9. https://docs.novelai.net/en/faq/
  10. https://blog.novelai.net/
  11. https://docs.novelai.net/en/subscription/
  12. https://blog.novelai.net/roadmap-pricing-launch-scaling-new-features-cfb7efa445eb
  13. https://docs.novelai.net/en/text/usersettings/usersettings/
  14. https://docs.novelai.net/en/text/models/
  15. https://blog.novelai.net/goodbye-calliope-ec114ea6d025
  16. https://blog.novelai.net/custom-ai-modules-dbc527d66081
  17. https://docs.novelai.net/en/text/modules/
  18. https://aituts.com/novelai-anime-image-generator/
  19. https://blog.novelai.net/introducing-novelai-diffusion-anime-v3-6d00d1c118c3
  20. https://docs.novelai.net/en/image/models/
  21. https://blog.novelai.net/release-novelai-anime-diffusion-v4-curated-preview-en-ca4b0b11e671
  22. https://blog.novelai.net/introducing-novelai-diffusion-v4-full-928e759620ea
  23. https://blog.novelai.net/novelai-diffusion-v4-5-full-release-678318c86205
  24. https://blog.novelai.net/novelai-diffusion-v4-5-curated-is-here-9e5ba1f628f3
  25. https://www.reddit.com/r/NovelAi/comments/1cam4u3/release_introducing_novelai_diffusion_furry_v3/
  26. https://docs.novelai.net/en/image/vibetransfer/
  27. https://docs.novelai.net/en/image/inpaint/
  28. https://docs.novelai.net/en/image/enhance/
  29. https://docs.novelai.net/en/image/
  30. https://novelai.net/image
  31. https://docs.novelai.net/en/text/glossary/
  32. https://docs.novelai.net/ja/text/jpmodules/
  33. https://docs.novelai.net/en/text/specialsymbols/
  34. https://blog.novelai.net/kickstarting-your-first-ai-assisted-story-a-beginners-guide-2bd6b98d119b
  35. https://docs.novelai.net/en/text/editor/
  36. https://www.tutorialspoint.com/novelai/novelai-quick-guide.htm
  37. https://www.blockchain-council.org/ai/how-to-use-novelai-text-generator/
  38. https://docs.novelai.net/en/text/lorebook/
  39. https://docs.novelai.net/en/text/editor/storysettings/
  40. https://sofiagray.com/blog/best-ai-for-erotica-top-nsfw-ai-story-generators/
  41. https://medium.com/@fffantasy2023/recommendations-for-nsfw-ai-writing-from-an-erotica-writer-b38e1b185fbc
  42. https://docs.novelai.net/en/text/specialmodules/
  43. https://docs.novelai.net/en/text/editor/writerstoolbox/
  44. https://docs.novelai.net/en/text/editor/advancedsettings/
  45. https://docs.novelai.net/en/image/tutorial-imgintro/
  46. https://arxiv.org/html/2409.15997v1
  47. https://docs.novelai.net/en/image/tutorial-artstyles/
  48. https://docs.novelai.net/en/text/usersettings/hotkeys/
  49. https://docs.novelai.net/en/image/basics/
  50. https://docs.novelai.net/en/image/controltools/
  51. https://docs.novelai.net/en/image/directortools/
  52. https://docs.novelai.net/en/text/usersettings/interface/
  53. https://docs.novelai.net/en/misc/specialevents/
  54. https://blog.novelai.net/image-generation-announcement-807b3cf0afec
  55. https://blog.novelai.net/introducing-novelai-lm-13b-402k-kayra-dabe8ff86fc6
  56. https://blog.novelai.net/introducing-novelai-diffusion-anime-v2-dc668ebca34b
  57. https://blog.novelai.net/muscle-up-with-llama-3-erato-3b48593a1cab
  58. https://x.com/novelaiofficial/status/1874906577515462963
  59. https://blog.novelai.net/text-model-release-introducing-glm-4-5-untuned-preview-for-novelai-opus-4aa866c8a0d5
  60. https://blog.novelai.net/text-model-update-glm-4-6-for-novelai-opus-44aceb5f72a7
  61. https://blog.novelai.net/text-model-release-glm-4-6-for-all-tiers-efc0a5445973
  62. https://blog.novelai.net/novelai-diffusion-v2-weights-release-b9d5fef5b9a4
  63. https://skywork.ai/blog/novelai-review-2025-text-anime-image-generation/
  64. https://humanizeai.now/blog/novelai-review-2024
  65. https://blog.novelai.net/en-ai-artist-spotlight-tutorial-tohofrog-tohofrog-3c0bfb832022
  66. https://www.reddit.com/r/NovelAi/comments/1j72btk/not_sure_what_the_issue_is_for_some_but_v4_is/
  67. https://www.reddit.com/r/NovelAi/comments/17im7od/official_were_celebrating_25_million_novelai/
  68. https://www.similarweb.com/website/novelai.net/
  69. https://gummysearch.com/r/NovelAi/
  70. https://discord.com/servers?query=novelai
  71. https://x.com/novelaiofficial/status/1699540671604854817
  72. https://medium.com/data-and-beyond/the-rise-of-uncensored-generative-ai-2d54ae8a8020
  73. https://www.reddit.com/r/NovelAi/comments/161cx1b/how_is_novel_ais_censorship_compared_to_sudowrite/
  74. https://tvtropes.org/pmwiki/pmwiki.php/Trivia/NovelAI
  75. https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/4516
  76. https://www.youtube.com/watch?v=Nt3v-RkeZy8
  77. https://nerdynav.com/sudowrite-review/
  78. https://techpoint.africa/guide/novelai-vs-ai-dungeon/
  79. https://dreamgen.com/blog/articles/novelai-review
  80. https://learn.g2.com/novel-ai-image-generation
  81. https://x.com/novelaiofficial/status/1578529189741080576
  82. https://www.reddit.com/r/StableDiffusion/comments/xysavk/has_anyone_tried_the_novelai_leak/
  83. https://www.reddit.com/r/sdforall/comments/yl3cek/moral_and_legal_ramifications_of_using_leaked/
  84. https://www.reddit.com/r/StableDiffusion/comments/1eytt42/novelai_decided_to_open_source_their_original_ai/
  85. https://blog.novelai.net/novelai-diffusion-v1-weights-release-en-e40d11e16bd5
  86. https://www.polygon.com/22408261/ai-dungeon-filter-controversy-minors-sexual-content-censorship-privacy-latitude
  87. https://community.openai.com/t/censorship-makes-writing-an-adult-novel-with-chatgpt-impossible/1065542
  88. https://docs.novelai.net/en/image/undesiredcontent/
  89. https://techcrunch.com/2022/08/24/deepfakes-for-all-uncensored-ai-art-model-prompts-ethics-questions/
  90. https://www.reddit.com/r/NovelAi/comments/xn3xp3/im_tired_of_hearing_this_when_people_talk_about/
  91. https://reelmind.ai/blog/the-best-ai-image-generator-for-nsfw-content
  92. https://novelai.net/terms
  93. https://arxiv.org/html/2506.14018
  94. https://artificialintelligenceact.eu/
Add your contribution
Related Hubs
User Avatar
No comments yet.