Available Models
The Morpheus Inference Marketplace provides access to a variety of open-source AI models. Models are hosted by providers in the decentralized marketplace, and availability may vary based on provider activity.Large Language Models (LLMs)
Flagship Models
These are the most capable models available for complex tasks.Reasoning Models
Models optimized for step-by-step thinking and complex problem solving.Mid-Size Models
Balanced performance and speed for most use cases.Fast Models
Optimized for speed and low latency.Proprietary, Anonymized Models
Frontier proprietary models served through anonymized providers on the Morpheus marketplace. These models are routed to closed-source frontier providers without exposing your identity to the upstream provider. Like all other models, each one supports web search by appending:web to the model name (e.g., claude-fable-5:web).
See Model Pricing for per-token rates for these models.
Embeddings Models
For vector embeddings and semantic search.Audio Models
Text-to-Speech
Model Capabilities
Function Calling
Function Calling
Models with function calling can invoke tools and APIs. Use the
tools parameter in your chat completion request to define available functions.Supported models: Most models except venice-uncensored and hermes-3-llama-3.1-405b. Includes glm-5.2, glm-5.1, glm-5.1-non-thinking, kimi-k2.7-code, kimi-k2.6, MiniMax-M2.7, and more.Reasoning
Reasoning
Reasoning models support extended thinking and step-by-step problem solving. They’re optimized for complex math, logic, and analytical tasks.Supported models:
glm-5.2, glm-5.1, glm-5, kimi-k2.7-code, kimi-k2.6, kimi-k2.5, glm-4.7-thinking, glm-4.7-flash, glm-4.7, minimax-m2.5, MiniMax-M2.7, arcee-trinity-large-thinking, gemma-4-26b-a4b, gemma-4-31b, deepseek-v4-pro, deepseek-v4-flashVision
Vision
Vision-capable models can analyze images passed in the messages array.Supported models:
mistral-31-24b, kimi-k2.6, kimi-k2.5, gemma-4-26b-a4b, gemma-4-31b, qwen35-35b-a3b, qwen35-9bWeb Search
Web Search
Any model can be upgraded with real-time web search by appending
:web to the model name. See the Web Search section below for details.Available for: All modelsCode Optimization
Code Optimization
Models specifically optimized for code generation and programming tasks.Supported models:
qwen3-coder-480b-a35b-instruct, glm-5.2, glm-5.1, glm-5, kimi-k2.7-code, kimi-k2.6, MiniMax-M2.7, minimax-m2.5, arcee-trinity-large-thinking, deepseek-v4-pro, deepseek-v4-flashWeb Search with :web
Every model listed above can be enhanced with real-time web search capabilities — you don’t need a separate model for it. Simply append :web to any model name, and the model will search the internet for current information before generating its response.
The model tables above only list base model names. To use any model with web search, just add
:web to the end. For example, llama-3.3-70b becomes llama-3.3-70b:web. This works universally across every model in the Morpheus marketplace.Using Models
Specify the model ID in your API requests:- curl
- Python
- JavaScript
List Active Models
Query the API to see currently available models:Model Selection Guide
Best for coding
Best for coding
deepseek-v4-pro- Frontier reasoning + coding, 1M context for whole-repo analysisqwen3-coder-480b-a35b-instruct- Top choice for code generation (256K context)kimi-k2.7-code- Next-gen agentic coding, parallel agent workflows (256K context)minimax-m2.5- SOTA agentic coding, full-stack development (198K context)glm-5.2- Next-gen agentic engineering, multi-file systems design (200K context)glm-5.1- Next-gen agentic engineering, multi-file systems design (200K context)MiniMax-M2.7- Cost-efficient agentic coding, tool orchestration (198K context)glm-5- Agentic engineering, multi-file systems design (200K context)arcee-trinity-large-thinking- Agentic coding, multi-turn tool calling (256K context)deepseek-v4-flash- Fast frontier-tier coding, 1M context at lower latencyllama-3.3-70b- Good balance of speed and quality
Best for long documents
Best for long documents
deepseek-v4-pro- 1M context, frontier reasoning over long documentsdeepseek-v4-flash- 1M context at lower latencyqwen3-next-80b- 256K context windowkimi-k2.7-code- 256K context with agentic codingkimi-k2.6- 256K context with multimodal reasoningkimi-k2.5- 256K context with multimodal reasoningqwen3-coder-480b-a35b-instruct- 256K context windowglm-5.2- 200K context, excellent at document analysisglm-5.1- 200K context, excellent at document analysisglm-5- 200K context, excellent at document analysisminimax-m2.5- 198K context windowarcee-trinity-large-thinking- 256K context, agentic reasoninggemma-4-31b- 256K context, multimodal reasoning
Best for speed
Best for speed
deepseek-v4-flash- Fast frontier-tier with 1M contextglm-4.7-flash- 30B MoE (3B active), 200K context, runs on consumer GPUsllama-3.2-3b- Very fast, 128K contextgemma-4-26b-a4b- MoE reasoning, near-4B inference speed (256K context)qwen35-9b- Fast with vision support (256K context)mistral-31-24b- Good speed with vision support
Best for reasoning
Best for reasoning
deepseek-v4-pro- Frontier reasoning, 1M context for ultra-long chainskimi-k2.7-code- Next-gen reasoning for code and agentic tasks, 256K contextkimi-k2.6- Next-gen math/logic benchmarks, multimodal, 256K contextkimi-k2.5- Top math/logic benchmarks (AIME 96%), multimodal, 256K contextglm-5.2- Next-gen agentic engineering, systems reasoning, 200K contextglm-5.1- Next-gen agentic engineering, systems reasoning, 200K contextglm-5- Agentic engineering, systems reasoning, 200K contextMiniMax-M2.7- Cost-efficient reasoning, agent workflows, 198K contextdeepseek-v4-flash- Fast frontier reasoning, 1M context at lower latencyglm-4.7-thinking- Extended thinking mode, 198K contextqwen3-235b- Complex analysis, 128K contextarcee-trinity-large-thinking- Agentic reasoning, multi-step planning, 256K contextgemma-4-31b- Math, science, visual reasoning, 256K context
Best for AI agents
Best for AI agents
minimax-m2.5- Purpose-built for agents, 80.2% SWE-Bench, multi-step tool orchestrationMiniMax-M2.7- Next-gen agents, cost-efficient orchestration, 198K contextglm-5.2- Next-gen long-horizon agentic tasks, advanced reasoning, 200K contextglm-5.1- Next-gen long-horizon agentic tasks, advanced reasoning, 200K contextglm-5- Long-horizon agentic tasks, #1 open-source on Vending Bench 2kimi-k2.7-code- Agent Swarm coding, parallel sub-agent workflows, 256K contextkimi-k2.6- Agent Swarm with up to 100 parallel sub-agentskimi-k2.5- Agent Swarm with up to 100 parallel sub-agentsarcee-trinity-large-thinking- Purpose-built for long-horizon agents, multi-turn tool callingglm-4.7-flash- Lightweight agentic coding, efficient tool-use workflows
Best for uncensored/creative
Best for uncensored/creative
venice-uncensored- Minimal content restrictions, roleplay
Next Steps
Quickstart
Get started making your first API call.
Chat Completions
Full API reference for chat completions.
Embeddings
Create embeddings for semantic search.
Text-to-Speech
Generate speech from text.

