Search the modelsyour product can ship.

sourceful/riverflow-v2-max-preview

Riverflow V2 Max Preview is the most powerful variant of Sourceful's Riverflow V2 preview lineup. This preview version exceeds the performance of Riverflow 1 Family and is Sourceful's first unified text-to-image and image-to-image model family. Pricing is $0.075 per output image, regardless of size. Sourceful imposes a 4.5MB request size limit, therefore it is highly recommended to pass image URLs instead of Base64 data.

sourceful/riverflow-v2-fast

Riverflow V2 Fast is the fastest variant of Sourceful's Riverflow 2.0 lineup, best for production deployments and latency-critical workflows. The Riverflow 2.0 series represents SOTA performance on image generation and editing tasks, using an integrated reasoning model to boost reliability and tackle complex challenges. Pricing is $0.02 per 1K output image and $0.04 per 2K output image. Does not support 4K image output. Additional features: - Custom font rendering via font_inputs ($0.03/font, max 2) - Image enhancement via super_resolution_references ($0.20/reference, max 4) See the image generation docs for details: https://openrouter.ai/docs/features/multimodal/image-generation Note: Sourceful imposes a 4.5MB request size limit, therefore it is highly recommended to pass image URLs instead of Base64 data.

sourceful/riverflow-v2-pro

Riverflow V2 Pro is the most powerful variant of Sourceful's Riverflow 2.0 lineup, best for top-tier control and perfect text rendering. The Riverflow 2.0 series represents SOTA performance on image generation and editing tasks, using an integrated reasoning model to boost reliability and tackle complex challenges. Pricing is $0.15 per 1K/2K output image and $0.33 per 4K output image. Additional features: - Custom font rendering via font_inputs ($0.03/font, max 2) - Image enhancement via super_resolution_references ($0.20/reference, max 4) See the image generation docs for details: https://openrouter.ai/docs/features/multimodal/image-generation Note: Sourceful imposes a 4.5MB request size limit, therefore it is highly recommended to pass image URLs instead of Base64 data.

allenai/molmo-2-8b

Molmo2-8B is an open vision-language model developed by the Allen Institute for AI (Ai2) as part of the Molmo2 family, supporting image, video, and multi-image understanding and grounding. It is based on Qwen3-8B and uses SigLIP 2 as its vision backbone, outperforming other open-weight, open-data models on short videos, counting, and captioning, while remaining competitive on long-video tasks.

openrouter/free

The simplest way to get free inference. openrouter/free is a router that selects free models at random from the models available on OpenRouter. The router smartly filters for models that support features needed for your request such as image understanding, tool calling, structured outputs and more.

openrouter/auto

Your prompt will be processed by a meta-model and routed to one of dozens of models (see below), optimizing for the best possible output. To see which model was used, visit [Activity](/activity), or read the `model` attribute of the response. Your response will be priced at the same rate as the routed model. Learn more, including how to customize the models for routing, in our [docs](/docs/guides/routing/routers/auto-router). Requests will be routed to the following models: - [anthropic/claude-haiku-4.5](/anthropic/claude-haiku-4.5) - [anthropic/claude-opus-4.6](/anthropic/claude-opus-4.6) - [anthropic/claude-sonnet-4.5](/anthropic/claude-sonnet-4.5) - [anthropic/claude-sonnet-4.6](/anthropic/claude-sonnet-4.6) - [deepseek/deepseek-r1](/deepseek/deepseek-r1) - [google/gemini-2.5-flash-lite](/google/gemini-2.5-flash-lite) - [google/gemini-3-flash-preview](/google/gemini-3-flash-preview) - [google/gemini-3-pro-preview](/google/gemini-3-pro-preview) - [google/gemini-3.1-pro-preview](/google/gemini-3.1-pro-preview) - [meta-llama/llama-3.3-70b-instruct](/meta-llama/llama-3.3-70b-instruct) - [minimax/minimax-m2.5](/minimax/minimax-m2.5) - [mistralai/codestral-2508](/mistralai/codestral-2508) - [mistralai/mistral-7b-instruct-v0.1](/mistralai/mistral-7b-instruct-v0.1) - [mistralai/mistral-large](/mistralai/mistral-large) - [mistralai/mistral-medium-3.1](/mistralai/mistral-medium-3.1) - [mistralai/mistral-small-3.2-24b-instruct-2506](/mistralai/mistral-small-3.2-24b-instruct-2506) - [moonshotai/kimi-k2-thinking](/moonshotai/kimi-k2-thinking) - [openai/gpt-5](/openai/gpt-5) - [openai/gpt-5-mini](/openai/gpt-5-mini) - [openai/gpt-5-nano](/openai/gpt-5-nano) - [openai/gpt-5.1](/openai/gpt-5.1) - [openai/gpt-5.2](/openai/gpt-5.2) - [openai/gpt-5.2-pro](/openai/gpt-5.2-pro) - [openai/gpt-5.3-chat](/openai/gpt-5.3-chat) - [openai/gpt-oss-120b](/openai/gpt-oss-120b) - [perplexity/sonar](/perplexity/sonar) - [qwen/qwen3-235b-a22b](/qwen/qwen3-235b-a22b) - [x-ai/grok-3](/x-ai/grok-3) - [x-ai/grok-3-mini](/x-ai/grok-3-mini) - [x-ai/grok-4](/x-ai/grok-4) - [x-ai/grok-4.1-fast](/x-ai/grok-4.1-fast) - [z-ai/glm-5](/z-ai/glm-5)

google/gemini-3-pro-preview

Gemini 3 Pro is Google’s flagship frontier model for high-precision multimodal reasoning, combining strong performance across text, image, video, audio, and code with a 1M-token context window. Reasoning Details must be preserved when using multi-turn tool calling, see our docs here: https://openrouter.ai/docs/use-cases/reasoning-tokens#preserving-reasoning-blocks. It delivers state-of-the-art benchmark results in general reasoning, STEM problem solving, factual QA, and multimodal understanding, including leading scores on LMArena, GPQA Diamond, MathArena Apex, MMMU-Pro, and Video-MMMU. Interactions emphasize depth and interpretability: the model is designed to infer intent with minimal prompting and produce direct, insight-focused responses. Built for advanced development and agentic workflows, Gemini 3 Pro provides robust tool-calling, long-horizon planning stability, and strong zero-shot generation for complex UI, visualization, and coding tasks. It excels at agentic coding (SWE-Bench Verified, Terminal-Bench 2.0), multimodal analysis, and structured long-form tasks such as research synthesis, planning, and interactive learning experiences. Suitable applications include autonomous agents, coding assistants, multimodal analytics, scientific reasoning, and high-context information processing.

google/gemini-3-pro-image-preview

Nano Banana Pro is Google’s most advanced image-generation and editing model, built on Gemini 3 Pro. It extends the original Nano Banana with significantly improved multimodal reasoning, real-world grounding, and high-fidelity visual synthesis. The model generates context-rich graphics, from infographics and diagrams to cinematic composites, and can incorporate real-time information via Search grounding. It offers industry-leading text rendering in images (including long passages and multilingual layouts), consistent multi-image blending, and accurate identity preservation across up to five subjects. Nano Banana Pro adds fine-grained creative controls such as localized edits, lighting and focus adjustments, camera transformations, and support for 2K/4K outputs and flexible aspect ratios. It is designed for professional-grade design, product visualization, storyboarding, and complex multi-element compositions while remaining efficient for general image creation workflows.

perplexity/sonar-pro-search

Exclusively available on the OpenRouter API, Sonar Pro's new Pro Search mode is Perplexity's most advanced agentic search system. It is designed for deeper reasoning and analysis. Pricing is based on tokens plus $18 per thousand requests. This model powers the Pro Search mode on the Perplexity platform. Sonar Pro Search adds autonomous, multi-step reasoning to Sonar Pro. So, instead of just one query + synthesis, it plans and executes entire research workflows using tools.

qwen/qwen3-vl-8b-thinking

Qwen3-VL-8B-Thinking is the reasoning-optimized variant of the Qwen3-VL-8B multimodal model, designed for advanced visual and textual reasoning across complex scenes, documents, and temporal sequences. It integrates enhanced multimodal alignment and long-context processing (native 256K, expandable to 1M tokens) for tasks such as scientific visual analysis, causal inference, and mathematical reasoning over image or video inputs. Compared to the Instruct edition, the Thinking version introduces deeper visual-language fusion and deliberate reasoning pathways that improve performance on long-chain logic tasks, STEM problem-solving, and multi-step video understanding. It achieves stronger temporal grounding via Interleaved-MRoPE and timestamp-aware embeddings, while maintaining robust OCR, multilingual comprehension, and text generation on par with large text-only LLMs.

bytedance-seed/seed-1.6-flash

Seed 1.6 Flash is an ultra-fast multimodal deep thinking model by ByteDance Seed, supporting both text and visual understanding. It features a 256k context window and can generate outputs of up to 16k tokens.

bytedance-seed/seed-1.6

Seed 1.6 is a general-purpose model released by the ByteDance Seed team. It incorporates multimodal capabilities and adaptive deep thinking with a 256K context window.

google/gemini-3-flash-preview

Gemini 3 Flash Preview is a high speed, high value thinking model designed for agentic workflows, multi turn chat, and coding assistance. It delivers near Pro level reasoning and tool use performance with substantially lower latency than larger Gemini variants, making it well suited for interactive development, long running agent loops, and collaborative coding tasks. Compared to Gemini 2.5 Flash, it provides broad quality improvements across reasoning, multimodal understanding, and reliability. The model supports a 1M token context window and multimodal inputs including text, images, audio, video, and PDFs, with text output. It includes configurable reasoning via thinking levels (minimal, low, medium, high), structured output, tool use, and automatic context caching. Gemini 3 Flash Preview is optimized for users who want strong reasoning and agentic behavior without the cost or latency of full scale frontier models.

mistralai/ministral-14b-2512

The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. A powerful and efficient language model with vision capabilities.

mistralai/ministral-8b-2512

A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.

mistralai/ministral-3b-2512

The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.

anthropic/claude-haiku-4.5

Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models. Matching Claude Sonnet 4’s performance across reasoning, coding, and computer-use tasks, Haiku 4.5 brings frontier-level capability to real-time and high-volume applications. It introduces extended thinking to the Haiku line; enabling controllable reasoning depth, summarized or interleaved thought output, and tool-assisted workflows with full support for coding, bash, web search, and computer-use tools. Scoring >73% on SWE-bench Verified, Haiku 4.5 ranks among the world’s best coding models while maintaining exceptional responsiveness for sub-agents, parallelized execution, and scaled deployment.

amazon/nova-2-lite-v1

Nova 2 Lite is a fast, cost-effective reasoning model for everyday workloads that can process text, images, and videos to generate text. Nova 2 Lite demonstrates standout capabilities in processing documents, extracting information from videos, generating code, providing accurate grounded answers, and automating multi-step agentic workflows.

mistralai/mistral-large-2512

Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.

openrouter/sherlock-think-alpha

This model was an early snapshot of Grok 4.1 Fast with reasoning enabled. Try the official launch of Grok 4.1 Fast [here](/x-ai/grok-4.1-fast) This is a cloaked model provided to the community to gather feedback. A frontier reasoning model that excels at tool calling, with a 1.8M context window and multimodal support. **Note:** All prompts and completions for this model are logged by the provider and may be used to improve the model.

openrouter/sherlock-dash-alpha

This model was an early snapshot of Grok 4.1 Fast with reasoning disabled. Try the official launch of Grok 4.1 Fast [here](/x-ai/grok-4.1-fast) This is a cloaked model provided to the community to gather feedback. A frontier non-reasoning model that excels at tool calling, with a 1.8M context window and multimodal support. **Note:** All prompts and completions for this model are logged by the provider and may be used to improve the model.

openrouter/polaris-alpha

This model was an early snapshot of GPT-5.1 with reasoning effort set to minimal. Try the official launch of GPT-5.1 [here](/openai/gpt-5.1) This is a cloaked model provided to the community to gather feedback. A powerful, general-purpose model that excels across real-world tasks, with standout performance in coding, tool calling, and instruction following. **Note:** All prompts and completions for this model are logged by the provider and may be used to improve the model.

amazon/nova-premier-v1

Amazon Nova Premier is the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models.

openrouter/andromeda-alpha

This model has been revealed as NVIDIA Nemotron Nano 2 VL. It continues to be offered for free by NVIDIA [here](https://openrouter.ai/nvidia/nemotron-nano-12b-v2-vl:free). This is a small reasoning VLM trained for image understanding. It's strengths include multi-image comprehension (6+ images), especially those containing charts and text. This is a cloaked model provided to the community to gather feedback. Note: All prompts and output are logged to improve the provider’s model and its product and services. Please do not upload any personal, confidential, or otherwise sensitive information. This is a trial use only. Do not use for production or business-critical systems.

qwen/qwen3-vl-8b-instruct

Qwen3-VL-8B-Instruct is a multimodal vision-language model from the Qwen3-VL series, built for high-fidelity understanding and reasoning across text, images, and video. It features improved multimodal fusion with Interleaved-MRoPE for long-horizon temporal reasoning, DeepStack for fine-grained visual-text alignment, and text-timestamp alignment for precise event localization. The model supports a native 256K-token context window, extensible to 1M tokens, and handles both static and dynamic media inputs for tasks like document parsing, visual question answering, spatial reasoning, and GUI control. It achieves text understanding comparable to leading LLMs while expanding OCR coverage to 32 languages and enhancing robustness under varied visual conditions.

openrouter/sonoma-dusk-alpha

This is a cloaked model provided to the community to gather feedback. A fast and intelligent general-purpose frontier model with a 2 million token context window. Supports image inputs and parallel tool calling. Note: It’s free to use during this testing period, and prompts and completions are logged by the model creator for feedback and training.

openrouter/sonoma-sky-alpha

This is a cloaked model provided to the community to gather feedback. A maximally intelligent general-purpose frontier model with a 2 million token context window. Supports image inputs and parallel tool calling. Note: It’s free to use during this testing period, and prompts and completions are logged by the model creator for feedback and training.

openrouter/horizon-beta

This is a cloaked model provided to the community to gather feedback. This is an improved version of [Horizon Alpha](/openrouter/horizon-alpha) Note: It’s free to use during this testing period, and prompts and completions are logged by the model creator for feedback and training.

openrouter/horizon-alpha

This was a cloaked model provided to the community to gather feedback. It has been deprecated - see [Horizon Beta](/openrouter/horizon-beta). Note: It’s free to use during this testing period, and prompts and completions are logged by the model creator for feedback and training.

openrouter/optimus-alpha

This is a cloaked model provided to the community to gather feedback. It's geared toward real world use cases, including programming. **Note:** All prompts and completions for this model are logged by the provider and may be used to improve the model.

openrouter/quasar-alpha

This is a cloaked model provided to the community to gather feedback. It’s a powerful, all-purpose model supporting long-context tasks, including code generation. **Note:** All prompts and completions for this model are logged by the provider and may be used to improve the model.

perplexity/sonar-reasoning-pro

Note: Sonar Pro pricing includes Perplexity search pricing. See [details here](https://docs.perplexity.ai/guides/pricing#detailed-pricing-breakdown-for-sonar-reasoning-pro-and-sonar-pro) Sonar Reasoning Pro is a premier reasoning model powered by DeepSeek R1 with Chain of Thought (CoT). Designed for advanced use cases, it supports in-depth, multi-step queries with a larger context window and can surface more citations per search, enabling more comprehensive and extensible responses.

perplexity/sonar-pro

Note: Sonar Pro pricing includes Perplexity search pricing. See [details here](https://docs.perplexity.ai/guides/pricing#detailed-pricing-breakdown-for-sonar-reasoning-pro-and-sonar-pro) For enterprises seeking more advanced capabilities, the Sonar Pro API can handle in-depth, multi-step queries with added extensibility, like double the number of citations per search as Sonar on average. Plus, with a larger context window, it can handle longer and more nuanced searches and follow-up questions.

perplexity/sonar

Sonar is lightweight, affordable, fast, and simple to use — now featuring citations and the ability to customize sources. It is designed for companies seeking to integrate lightweight question-and-answer features optimized for speed.