Body Builder (beta)

Auto Router (Beta) is a task-aware router from OpenRouter. It classifies each request, then routes it the most popular model for that task based on aggregate spend, filtered by your selected cost-quality tradeoff.

To see which model was used, visit 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. For another way to route, see Pareto Code.

Fusion turns your prompt into a small multi-model deliberation. A panel of expert models (see below) analyzes your prompt in parallel with web search and web fetch enabled, then a judge model synthesizes their responses into a structured analysis — consensus, contradictions, partial coverage, unique insights, and blind spots — and writes the final answer from it.

By default the panel is the Quality preset; switch to Budget for cheaper members, or override the panel and judge entirely with the fusion plugin's analysis_models and model fields. Reach for Fusion when a single model isn't enough — research, expert critique, or anywhere the cost of being wrong outweighs a few extra completions.

Because Fusion runs every panel member plus a judge call, your request is priced as the sum of those underlying completions rather than a single model. To see which models ran, visit Activity.

Note: Context limits are dependent on which models you select.

Learn more in our docs. For another way to route, see the Auto Router.

Owl Alpha is a high-performance foundation model designed for agentic workloads. Natively supports tool use, and long-context tasks, with strong performance in code generation, automated workflows, and complex instruction execution. Compatible with Claude Code, OpenClaw, and other mainstream productivity tools.

Note: Prompts and completions may be logged by the provider and used to improve the model.

The Pareto Router maintains a tiered shortlist of strong coding models, ranked by Artificial Analysis coding percentiles. Set min_coding_score between 0 and 1 on the pareto-router plugin to control how strong a coder you need; higher scores select stronger (and typically more expensive) models. If you omit min_coding_score, the router defaults to the High tier.

Selecting Nitro from the variant dropdown ranks the models in your tier by measured throughput and routes each request to the fastest one, so you trade some model variety for lower latency.

Read the Pareto Router docs for the full selection logic, fallback behavior, and how to customize routing. For another way to route, see the Auto Router.

Elephant Alpha is a 100B-parameter text model focused on intelligence efficiency, delivering strong performance while minimizing token usage. It supports a 256K context window with up to 32K output tokens, function calling, structured output, and prompt caching. It is particularly well-suited for code completion and debugging, rapid document processing, and lightweight agent interactions.

Note: Prompts and completions may be logged by the provider and used to improve the model.

Hunter Alpha is a 1 Trillion parameter + 1M token context frontier intelligence model built for agentic use. It excels at long-horizon planning, complex reasoning, and sustained multi-step task execution, with the reliability and instruction-following precision that frameworks like OpenClaw need.

Note: All prompts and completions for this model are logged by the provider and may be used to improve the model.

Healer Alpha is a frontier omni-modal model with vision, hearing, reasoning, and action capabilities. It brings the full power of agentic intelligence into the real world: natively perceiving visual and audio inputs, reasoning across modalities, and executing complex multi-step tasks with precision and reliability.

Note: All prompts and completions for this model are logged by the provider and may be used to improve the model.

This is a cloaked model provided to the community to gather feedback. A reasoning model designed for speed. It is built for coding assistants, real-time conversational applications, and agentic workflows.

Default reasoning effort is set to medium for fast responses. For agentic coding use cases, we recommend changing effort to high.

Note: All prompts and completions for this model are logged by the provider and may be used to improve the model.

Pony is a cutting-edge foundation model with strong performance in coding, agentic workflows, reasoning, and roleplay, making it well suited for hands-on coding and real-world use.

Note: All prompts and completions for this model are logged by the provider and may be used to improve the model.

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.

This model was an early testing version of Mistral Large 3. Try the official launch of Mistral Large 3 here

This is a cloaked model provided to the community to gather feedback. A general-purpose multimodal model (text/image in, text out) designed for reliability, long-context comprehension, and adaptive logic. It is engineered for production-grade assistants, retrieval-augmented systems, science workloads, and complex agentic workflows.

Note: All prompts and completions for this model are logged by the provider and may be used to improve the model.

This model was an early snapshot of Grok 4.1 Fast with reasoning disabled. Try the official launch of Grok 4.1 Fast here

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.

This model was an early snapshot of Grok 4.1 Fast with reasoning enabled. Try the official launch of Grok 4.1 Fast here

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.

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

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.

This model has been revealed as NVIDIA Nemotron Nano 2 VL. It continues to be offered for free by NVIDIA here.

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.

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.

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.

This is a cloaked model provided to the community to gather feedback. This is an improved version of 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.

This was a cloaked model provided to the community to gather feedback. It has been deprecated - see 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.

This is a cloaked model provided to the community to gather feedback. It's an all-purpose model supporting real-world, 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 and other products and services. You remain responsible for any required end user notices and consents and for ensuring that no personal, confidential, or otherwise sensitive information, including data from individuals under the age of 18, is submitted.

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.

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.

This model is under development. Check the OpenRouter Discord for updates.

The Auto Router automatically selects the best model for your prompt, powered by the wisdom of the market. It routes you based on what the OpenRouter community collectively spends on for exactly the kind of task your prompt represents. It looks at spend over a trailing 7-day window, so it stays up to date with new model releases automatically.

Your response will be priced at the same rate as the routed model. The cost_tier setting (low, medium, high, xhigh, or max) selects how much you're willing to pay. The default is low, giving you a highly cost-efficient set of models. When selecting models, the auto router respects any guardrails, privacy/ZDR policies, and model restrictions you have in the request or account settings. Multi-turn conversations stick to one model until it is no longer a leading choice for your task.

Learn more in our docs. For another way to route, see Pareto Code.