Auto Router

Auto Code is OpenRouter’s router built specifically for coding agents and harnesses. It uses the same routing engine as the Auto Router, with every request treated as part of an agent session and model choices guided by coding-task pass rate, completion time, and cost per solved task.

It follows edits, test results, and recurring errors across turns, keeping the model while work is going well and trying more reasoning effort before switching when trouble persists. Its default coding tier starts from stronger models and weighs failed code changes more heavily. Your model and provider restrictions still apply.

The experimental version of our Auto Router where we test new improvements. Use it to get the latest and greatest version of our general purpose auto router, but expect beta quality. When new improvements are proven in auto-beta, we graduate them to the auto router. We've love to hear your feedback on whether auto-beta is working for you, or requests for routing improvements.

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.

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.

Transform your natural language requests into structured OpenRouter API request objects. Describe what you want to accomplish with AI models, and Body Builder will construct the appropriate API calls. Example: "count to 10 using gemini and opus."

This is useful for creating multi-model requests, custom model routers, or programmatic generation of API calls from human descriptions.

BETA NOTICE: Body Builder is in beta, and currently free. Pricing and functionality may change in the future.

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.