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Mistral Small 3.1 24B

By Mistral. 24.0 billion parameters, a context window of 128,000 tokens and the licence apache-2.0.

Facts

Released
2025-03-11 the day the repository was first published on Hugging Face Hugging Face, read
Licence
apache-2.0 the licence the model card declares Hugging Face, read
Open weights
Yes the weights are published in this Hugging Face repository Hugging Face, read
Parameters
24.0 billion counted from the safetensors weight files Hugging Face, read
Active parameters
Unknown
Knowledge cutoff
2023-10-31 the knowledge cutoff OpenRouter lists OpenRouter, read
Context window
  • 128,000 tokens the context length OpenRouter lists OpenRouter, read
Longest output
  • 102,400 tokens the largest output OpenRouter's first provider allows OpenRouter, read
Tool calling
  • Yes OpenRouter lists tools among the supported parameters OpenRouter, read
Structured output
  • No OpenRouter lists no structured output parameter OpenRouter, read
Reasoning controls
Unknown
Inputs and outputs
text, image in, text out OpenRouter, read
Good for
  • Vision: OpenRouter lists images among its inputs OpenRouter, read

Prices

Prices in US dollars per million tokens, as each source lists them
ProviderInputOutputContextAs ofSource
Cloudflare through OpenRouter0.351 USD0.555 USD128,000OpenRouter endpoints, read

Run it on your own hardware

Weights are the sizes of the files a source lists, or an estimate from the parameter count where none does. Memory is an estimate: weights plus KV cache plus 512 MiB and 5 percent of the weights for runtime buffers. Check it against your hardware.

QuantizationWeightsMemory at 8,192 tokensMemory at 32,768 tokens
F16 estimate44.7 GiBUnknown: no KV cache numbersUnknown: no KV cache numbers
Q8_0 estimate23.8 GiBUnknown: no KV cache numbersUnknown: no KV cache numbers
Q4_0 estimate12.6 GiBUnknown: no KV cache numbersUnknown: no KV cache numbers

Start it with a local runtime

  • vLLM
    vllm serve mistralai/Mistral-Small-3.1-24B-Instruct-2503
  • SGLang
    sglang serve --model-path mistralai/Mistral-Small-3.1-24B-Instruct-2503 --port 30000

Use it from your harness

Set up for OpenRouter with the model mistralai/mistral-small-3.1-24b-instruct. Each endpoint page has the same setup for its own address.

OpenCode

Put this in opencode.json in your project folder:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "openrouter": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "OpenRouter",
      "options": {
        "baseURL": "https://openrouter.ai/api/v1",
        "apiKey": "{env:OPENROUTER_API_KEY}"
      },
      "models": {
        "mistralai/mistral-small-3.1-24b-instruct": {
          "name": "Mistral Small 3.1 24B",
          "limit": {
            "context": 128000,
            "output": 102400
          }
        }
      }
    }
  }
}
  • OpenCode reads any OpenAI-compatible address through the @ai-sdk/openai-compatible package, and an address that speaks the Responses API through @ai-sdk/openai.

From OpenCode documentation, read .

Pi

Put this in ~/.pi/agent/models.json:

{
  "providers": {
    "openrouter": {
      "baseUrl": "https://openrouter.ai/api/v1",
      "api": "openai-completions",
      "apiKey": "$OPENROUTER_API_KEY",
      "models": [
        {
          "id": "mistralai/mistral-small-3.1-24b-instruct"
        }
      ]
    }
  }
}
  • The apiKey field can name an environment variable as $NAME.

From Pi documentation, read .

Codex

Put this in ~/.codex/config.toml:

model = "mistralai/mistral-small-3.1-24b-instruct"
model_provider = "openrouter"

[model_providers.openrouter]
name = "OpenRouter"
base_url = "https://openrouter.ai/api/v1"
env_key = "OPENROUTER_API_KEY"
  • Codex speaks the Responses API only: responses is the one supported wire API of a custom provider. Ollama and LM Studio are built in and start with --oss.

From Codex documentation, read .

Claude Code

Put this in ~/.claude/settings.json, or variables in your shell:

export ANTHROPIC_BASE_URL="https://openrouter.ai/api"
export ANTHROPIC_AUTH_TOKEN="$OPENROUTER_API_KEY"
export ANTHROPIC_MODEL="mistralai/mistral-small-3.1-24b-instruct"
claude
  • Claude Code sends Anthropic Messages requests to ANTHROPIC_BASE_URL. Anthropic says it does not support routing Claude Code to models other than Claude through any gateway, so some features may not work with another model.

From Claude Code documentation, read .

Published results

These are results other people published. Baltor did not run them and does not rank models by them.