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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

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 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-flash
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, qwen35-9b
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 models
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-flash

Web 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.
Verify exact model names — including :web variants — by querying the /models endpoint. The :web suffix is universal, but the base model name must match exactly what the API returns.

Using Models

Specify the model ID in your API requests:

List Active Models

Query the API to see currently available models:
Model availability depends on active providers in the Morpheus Inference Marketplace. The API automatically routes your request to the highest-rated provider for your selected model.

Model Selection Guide

  • deepseek-v4-pro - Frontier reasoning + coding, 1M context for whole-repo analysis
  • qwen3-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 latency
  • llama-3.3-70b - Good balance of speed and quality
  • deepseek-v4-pro - 1M context, frontier reasoning over long documents
  • deepseek-v4-flash - 1M context at lower latency
  • qwen3-next-80b - 256K context window
  • kimi-k2.7-code - 256K context with agentic coding
  • kimi-k2.6 - 256K context with multimodal reasoning
  • kimi-k2.5 - 256K context with multimodal reasoning
  • qwen3-coder-480b-a35b-instruct - 256K context window
  • glm-5.2 - 200K context, excellent at document analysis
  • glm-5.1 - 200K context, excellent at document analysis
  • glm-5 - 200K context, excellent at document analysis
  • minimax-m2.5 - 198K context window
  • arcee-trinity-large-thinking - 256K context, agentic reasoning
  • gemma-4-31b - 256K context, multimodal reasoning
  • deepseek-v4-flash - Fast frontier-tier with 1M context
  • glm-4.7-flash - 30B MoE (3B active), 200K context, runs on consumer GPUs
  • llama-3.2-3b - Very fast, 128K context
  • gemma-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
  • deepseek-v4-pro - Frontier reasoning, 1M context for ultra-long chains
  • kimi-k2.7-code - Next-gen reasoning for code and agentic tasks, 256K context
  • kimi-k2.6 - Next-gen math/logic benchmarks, multimodal, 256K context
  • kimi-k2.5 - Top math/logic benchmarks (AIME 96%), multimodal, 256K context
  • glm-5.2 - Next-gen agentic engineering, systems reasoning, 200K context
  • glm-5.1 - Next-gen agentic engineering, systems reasoning, 200K context
  • glm-5 - Agentic engineering, systems reasoning, 200K context
  • MiniMax-M2.7 - Cost-efficient reasoning, agent workflows, 198K context
  • deepseek-v4-flash - Fast frontier reasoning, 1M context at lower latency
  • glm-4.7-thinking - Extended thinking mode, 198K context
  • qwen3-235b - Complex analysis, 128K context
  • arcee-trinity-large-thinking - Agentic reasoning, multi-step planning, 256K context
  • gemma-4-31b - Math, science, visual reasoning, 256K context
  • minimax-m2.5 - Purpose-built for agents, 80.2% SWE-Bench, multi-step tool orchestration
  • MiniMax-M2.7 - Next-gen agents, cost-efficient orchestration, 198K context
  • glm-5.2 - Next-gen long-horizon agentic tasks, advanced reasoning, 200K context
  • glm-5.1 - Next-gen long-horizon agentic tasks, advanced reasoning, 200K context
  • glm-5 - Long-horizon agentic tasks, #1 open-source on Vending Bench 2
  • kimi-k2.7-code - Agent Swarm coding, parallel sub-agent workflows, 256K context
  • kimi-k2.6 - Agent Swarm with up to 100 parallel sub-agents
  • kimi-k2.5 - Agent Swarm with up to 100 parallel sub-agents
  • arcee-trinity-large-thinking - Purpose-built for long-horizon agents, multi-turn tool calling
  • glm-4.7-flash - Lightweight agentic coding, efficient tool-use workflows
  • 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.