Model Reference

This page lists recommended models for AgentUse, organized by provider.

Note: Other models from these providers may also work. These are the ones we recommend and test against.

Auto-generated: Run pnpm generate:models to update.

Quick Reference

Default models:

Anthropic: anthropic:claude-sonnet-5-5 (balanced performance)
OpenAI: openai:gpt-5.6 (general-purpose GPT)
OpenRouter: openrouter:z-ai/glm-5.3 (open source)
OpenCode Go: opencode-go:gpt-6-luna (open coding models)
Amazon Bedrock: bedrock:us.anthropic.claude-sonnet-4-5-20250929-v1:0

Version Aliases

Leave the version off a model id and you get whichever release is current, so an agent file does not need editing every time a new model ships:

---
model: anthropic:claude-sonnet   # -> anthropic:claude-sonnet-5-5 today
---

Aliases follow the lineup below, which is refreshed per AgentUse release. An id that exists for real always wins, so nothing you pin can be reinterpreted.

Alias	Currently resolves to
`anthropic:claude-opus`	`anthropic:claude-opus-5-5`
`anthropic:claude-haiku`	`anthropic:claude-haiku-5-5`
`anthropic:claude-sonnet`	`anthropic:claude-sonnet-5-5`
`anthropic:claude-fable`	`anthropic:claude-fable-5-1`
`openai:gpt-sol`	`openai:gpt-6.1-sol`
`openai:gpt-luna`	`openai:gpt-6-luna`
`openai:gpt-astra`	`openai:gpt-6-astra`
`openai:gpt`	`openai:gpt-5.6`
`openai:gpt-terra`	`openai:gpt-5.6-terra`
`openai:gpt-pro`	`openai:gpt-5.5-pro`
`openai:gpt-nano`	`openai:gpt-5.4-nano`
`openai:gpt-mini`	`openai:gpt-5.4-mini`
`openai:gpt-codex`	`openai:gpt-5.3-codex`
`openai:gpt-codex-spark`	`openai:gpt-5.3-codex-spark`
`openai:gpt-chat-latest`	`openai:gpt-5.3-chat-latest`
`openrouter:z-ai/glm`	`openrouter:z-ai/glm-5.3`
`openrouter:z-ai/glm-prime`	`openrouter:z-ai/glm-5.3-prime`
`openrouter:z-ai/glm-flash`	`openrouter:z-ai/glm-5.3-flash`
`openrouter:z-ai/glm-flashx`	`openrouter:z-ai/glm-5.3-flashx`
`openrouter:z-ai/glm-turbo`	`openrouter:z-ai/glm-5v-turbo`
`openrouter:x-ai/grok`	`openrouter:x-ai/grok-4.7`
`openrouter:deepseek/deepseek-pro`	`openrouter:deepseek/deepseek-v4-pro`
`openrouter:deepseek/deepseek-flash`	`openrouter:deepseek/deepseek-v4-flash`
`openrouter:qwen/qwen-max`	`openrouter:qwen/qwen3.8-max-0902`
`openrouter:google/gemini-flash`	`openrouter:google/gemini-3.8-flash`
`openrouter:google/gemini-pro-preview`	`openrouter:google/gemini-3.1-pro-preview`
`openrouter:minimax/minimax`	`openrouter:minimax/minimax-m3`
`openrouter:moonshotai/kimi`	`openrouter:moonshotai/kimi-k3`
`openrouter:google/gemini-flash-preview`	`openrouter:google/gemini-3-flash-preview`
`opencode-go:gpt-luna`	`opencode-go:gpt-6-luna`
`opencode-go:glm`	`opencode-go:glm-5.3`
`opencode-go:glm-flash`	`opencode-go:glm-5.3-flash`
`opencode-go:grok`	`opencode-go:grok-4.7`
`opencode-go:hy-preview`	`opencode-go:hy4-preview`
`opencode-go:deepseek-pro`	`opencode-go:deepseek-v4-pro`
`opencode-go:qwen-max`	`opencode-go:qwen3.8-max`
`opencode-go:qwen-flash`	`opencode-go:qwen3.8-flash`
`opencode-go:qwen-plus`	`opencode-go:qwen3.7-plus`
`opencode-go:kimi`	`opencode-go:kimi-k3`
`opencode-go:minimax`	`opencode-go:minimax-m3`
`opencode-go:kimi-code`	`opencode-go:kimi-k2.7-code`
`opencode-go:mimo-pro`	`opencode-go:mimo-v2.6-pro`
`opencode-go:mimo`	`opencode-go:mimo-v2.5`

Run agentuse models to see what each alias resolves to on your install, and agentuse models unpin to convert pinned ids in your agent files into aliases. To name your own, add a models.aliases block to ~/.agentuse/config.json and reference it with the @ sigil (see Configuration Files):

{ "models": { "default": "anthropic:claude-sonnet", "aliases": { "fast": "anthropic:claude-haiku" } } }

---
model: "@fast"
---

Aliases can include a reasoning preset. Use reasoning, the same field as agent frontmatter, and give each fallback its own setting:

{
  "models": {
    "aliases": {
      "astra-high": { "model": "openai:gpt-6-astra", "reasoning": "high" },
      "deep": {
        "candidates": [
          "@astra-high",
          { "model": "anthropic:claude-opus", "reasoning": "high" },
          { "model": "openai:gpt", "reasoning": "medium" }
        ],
        "cooldown": "1m"
      }
    }
  }
}

Select this chain with model: "@deep". A candidate’s explicit reasoning takes precedence over agent frontmatter. Candidates without a preset use the agent’s reasoning setting, or the model default when that is omitted. Effort is never inherited from the previous candidate. Existing model-specific reasoning compatibility rules still apply. Presets support none, minimal, low, medium, high, xhigh, and max. agentuse models shows configured effort alongside each resolved candidate. The resolved settings are captured with the session for approval resume and with run-wide model overrides. If a preset references another fallback alias, its reasoning override applies only to that alias’s primary candidate. Repeating a concrete model with conflicting reasoning settings is a configuration error. Named aliases may also define ordered fallback candidates and an in-memory cooldown. See Model defaults and aliases.

Recommended Models

Anthropic

Model ID	Name	Input Context	Output	Capabilities
`anthropic:claude-opus-5-5`	Claude Opus 5.5	1,000,000	128,000	Reasoning, Vision, Tools
`anthropic:claude-haiku-5-5`	Claude Haiku 5.5	1,000,000	128,000	Reasoning, Vision, Tools
`anthropic:claude-sonnet-5-5`	Claude Sonnet 5.5	1,000,000	128,000	Reasoning, Vision, Tools
`anthropic:claude-fable-5-1`	Claude Fable 5.1	1,000,000	128,000	Reasoning, Vision, Tools

OpenAI

Model ID	Name	Input Context	Output	Capabilities
`openai:gpt-6.1-sol`	GPT-6.1 Sol	922,000	128,000	Reasoning, Vision, Tools
`openai:gpt-6-luna`	GPT-6 Luna	922,000	128,000	Reasoning, Vision, Tools
`openai:gpt-6-astra`	GPT-6 Astra	922,000	128,000	Reasoning, Vision, Tools
`openai:gpt-5.6`	GPT-5.6	922,000	128,000	Reasoning, Vision, Tools
`openai:gpt-5.6-terra`	GPT-5.6 Terra	922,000	128,000	Reasoning, Vision, Tools
`openai:gpt-5.5-pro`	GPT-5.5 Pro	922,000	128,000	Reasoning, Vision, Tools
`openai:gpt-5.4-nano`	GPT-5.4 nano	272,000	128,000	Reasoning, Vision, Tools
`openai:gpt-5.4-mini`	GPT-5.4 mini	272,000	128,000	Reasoning, Vision, Tools
`openai:gpt-5.3-codex`	GPT-5.3 Codex	272,000	128,000	Reasoning, Vision, Tools
`openai:gpt-5.3-codex-spark`	GPT-5.3 Codex Spark	100,000	32,000	Reasoning, Vision, Tools
`openai:gpt-5.3-chat-latest`	GPT-5.3 Chat (latest)	128,000	16,384	Vision, Tools

OpenRouter

Model ID	Name	Input Context	Output	Capabilities
`openrouter:z-ai/glm-5.3`	GLM-5.3	1,048,576	943,718	Reasoning, Tools
`openrouter:z-ai/glm-5.3-prime`	GLM 5.3 Prime	1,000,000	131,072	Reasoning, Tools
`openrouter:z-ai/glm-5.3-flash`	GLM-5.3-Flash	1,048,576	943,717	Reasoning, Vision, Tools
`openrouter:z-ai/glm-5.3-flashx`	GLM 5.3 FlashX	1,048,576	131,072	Reasoning, Vision, Tools
`openrouter:z-ai/glm-5v-turbo`	GLM-5V-Turbo	202,752	131,072	Reasoning, Vision, Tools
`openrouter:x-ai/grok-4.7`	Grok 4.7	500,000	450,000	Reasoning, Vision, Tools
`openrouter:deepseek/deepseek-v4-pro`	DeepSeek V4 Pro	1,048,576	384,000	Reasoning, Tools
`openrouter:deepseek/deepseek-v4-flash`	DeepSeek V4 Flash	1,048,576	943,717	Reasoning, Tools
`openrouter:qwen/qwen3.8-max-0902`	Qwen3.8 Max 0902	1,000,000	131,072	Reasoning, Vision, Tools
`openrouter:google/gemini-3.8-flash`	Gemini 3.8 Flash	1,048,576	65,536	Reasoning, Vision, Tools
`openrouter:qwen/qwen3.7-plus`	Qwen3.7 Plus	1,000,000	131,072	Reasoning, Vision, Tools
`openrouter:google/gemini-3.1-pro-preview`	Gemini 3.1 Pro Preview	1,048,576	65,536	Reasoning, Vision, Tools
`openrouter:minimax/minimax-m3`	MiniMax-M3	1,048,576	512,000	Reasoning, Vision, Tools
`openrouter:moonshotai/kimi-k3`	Kimi K3	1,048,576	943,718	Reasoning, Vision, Tools
`openrouter:google/gemini-3-flash-preview`	Gemini 3 Flash Preview	1,048,576	65,536	Reasoning, Vision, Tools

OpenCode Go

Model ID	Name	Input Context	Output	Capabilities
`opencode-go:gpt-6-luna`	GPT-6 Luna	922,000	128,000	Reasoning, Vision, Tools
`opencode-go:glm-5.3`	GLM-5.3	1,000,000	131,072	Reasoning, Tools
`opencode-go:glm-5.3-flash`	GLM-5.3-Flash	1,000,000	131,072	Reasoning, Vision, Tools
`opencode-go:grok-4.7`	Grok 4.7	500,000	500,000	Reasoning, Vision, Tools
`opencode-go:hy4-preview`	Hy4 preview	1,024,000	64,000	Reasoning, Tools
`opencode-go:deepseek-v4-pro`	DeepSeek V4 Pro (New)	1,000,000	384,000	Reasoning, Tools
`opencode-go:qwen3.8-max`	Qwen3.8 Max	1,000,000	131,072	Reasoning, Vision, Tools
`opencode-go:qwen3.8-flash`	Qwen3.8 Flash	1,000,000	131,072	Reasoning, Vision, Tools
`opencode-go:qwen3.7-plus`	Qwen3.7 Plus	1,000,000	65,536	Reasoning, Vision, Tools
`opencode-go:kimi-k3`	Kimi K3	1,048,576	131,072	Reasoning, Vision, Tools
`opencode-go:minimax-m3`	MiniMax-M3	1,000,000	131,072	Reasoning, Vision, Tools
`opencode-go:kimi-k2.7-code`	Kimi K2.7 Code	262,144	262,144	Reasoning, Vision, Tools
`opencode-go:mimo-v2.6-pro`	MiMo-V2.6-Pro	1,048,576	131,072	Reasoning, Vision, Tools
`opencode-go:mimo-v2.5`	MiMo V2.5	1,000,000	128,000	Reasoning, Vision, Tools

Amazon Bedrock

Bedrock model IDs are passed through unchanged and are not validated against the static registry. Use any model ID supported by your AWS account and region.

Model ID (example)	Notes
`bedrock:us.anthropic.claude-sonnet-4-5-20250929-v1:0`	Claude Sonnet 4.5 (US cross-region inference profile)
`bedrock:anthropic.claude-3-5-sonnet-20241022-v2:0`	Claude 3.5 Sonnet v2
`bedrock:anthropic.claude-3-haiku-20240307-v1:0`	Claude 3 Haiku
`bedrock:meta.llama3-70b-instruct-v1:0`	Llama 3 70B Instruct
`bedrock:mistral.mistral-large-2402-v1:0`	Mistral Large
`bedrock:us.amazon.nova-pro-v1:0`	Amazon Nova Pro

See the Amazon Bedrock model catalog for the full list. Model availability depends on the AWS region and on the model access granted in your account. Authentication uses standard AWS environment variables (AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY / AWS_REGION, optional AWS_SESSION_TOKEN) or AWS_BEARER_TOKEN_BEDROCK. See the Model Configuration guide for details.

Custom Providers

In addition to the built-in providers above, Dashboard Settings can connect custom OpenAI Chat Completions, OpenAI Responses, or Anthropic Messages endpoints. It discovers and saves available models and verifies the selected protocol with a minimal completion. For OpenAI-compatible local endpoints, you can also use the CLI:

# Add Ollama
agentuse provider add ollama --url http://localhost:11434/v1

# Add LM Studio
agentuse provider add lmstudio --url http://localhost:1234/v1

Then use any model available on those endpoints:

agentuse run agent.agentuse -m ollama:glm-5-flash:q4_K_M
agentuse run agent.agentuse -m ollama:qwen3.5:0.8b
agentuse run agent.agentuse -m lmstudio:qwen/qwen3.5-9b

See Model Configuration for full setup details.

Usage

Specify a model in your agent file, pinned to a version or tracking the line:

---
model: anthropic:claude-sonnet-5-5   # pinned
---

---
model: anthropic:claude-sonnet     # newest in this line
---

Omit model entirely to use the configured default (models.default or AGENTUSE_MODEL). Or override via CLI, which accepts the same aliases:

agentuse run agent.agentuse -m openai:gpt-5.6
agentuse run agent.agentuse -m openai:gpt
agentuse run agent.agentuse -m ollama:glm-5-flash:q4_K_M

Getting Started

Building

Running

Reference

Model Reference

Model Reference

Quick Reference

Version Aliases

Recommended Models

Anthropic

OpenAI

OpenRouter

OpenCode Go

Amazon Bedrock

Custom Providers

Usage

​Model Reference

​Quick Reference

​Version Aliases

​Recommended Models

​Anthropic

​OpenAI

​OpenRouter

​OpenCode Go

​Amazon Bedrock

​Custom Providers

​Usage

Model Reference

Quick Reference

Version Aliases

Recommended Models

Anthropic

OpenAI

OpenRouter

OpenCode Go

Amazon Bedrock

Custom Providers

Usage