Mistral-Small-24B-Instruct-2501-GGUF

Original Model

mistralai/Mistral-Small-24B-Instruct-2501

Run with LlamaEdge

  • LlamaEdge version: v0.16.4

  • Prompt template

    • Chat

      • Prompt type: mistral-small-chat

      • Prompt string

        <s>[SYSTEM_PROMPT]<system prompt>[/SYSTEM_PROMPT][INST]<user message>[/INST]<assistant response></s>[INST]<user message>[/INST]
        
    • Chat + Tool Use

      • Prompt type: mistral-small-tool

      • Prompt string

        <s>[INST] {user_message_1}[/INST][TOOL_CALLS] [{tool_call_1},{tool_call_2}]</s>[TOOL_RESULTS] {tool_result_1}[/TOOL_RESULTS] {assistant_message_1}</s>[AVAILABLE_TOOLS] [{tool_1},{tool_2}][/AVAILABLE_TOOLS][INST] {system_message}<0x0A><0x0A>{user_message_2}[/INST]
        
  • Context size: 32000

  • Run as LlamaEdge service

    • Chat

      wasmedge --dir .:. --nn-preload default:GGML:AUTO:Mistral-Small-24B-Instruct-2501-Q5_K_M.gguf \
          llama-api-server.wasm \
          --prompt-template mistral-small-chat \
          --ctx-size 32000 \
          --model-name Mistral-Small-24B-Instruct-2501
      
    • Chat + Tool Use

      wasmedge --dir .:. --nn-preload default:GGML:AUTO:Mistral-Small-24B-Instruct-2501-Q5_K_M.gguf \
          llama-api-server.wasm \
          --prompt-template mistral-small-tool \
          --ctx-size 32000 \
          --model-name Mistral-Small-24B-Instruct-2501
      

      Example:

      image/png

  • Run as LlamaEdge command app

    • Chat

      wasmedge --dir .:. --nn-preload default:GGML:AUTO:Mistral-Small-24B-Instruct-2501-Q5_K_M.gguf \
        llama-chat.wasm \
        --prompt-template mistral-small-chat \
        --ctx-size 32000
      

Quantized GGUF Models

Name Quant method Bits Size Use case
Mistral-Small-24B-Instruct-2501-Q2_K.gguf Q2_K 2 8.89 GB smallest, significant quality loss - not recommended for most purposes
Mistral-Small-24B-Instruct-2501-Q3_K_L.gguf Q3_K_L 3 12.4 GB small, substantial quality loss
Mistral-Small-24B-Instruct-2501-Q3_K_M.gguf Q3_K_M 3 11.5 GB very small, high quality loss
Mistral-Small-24B-Instruct-2501-Q3_K_S.gguf Q3_K_S 3 10.4 GB very small, high quality loss
Mistral-Small-24B-Instruct-2501-Q4_0.gguf Q4_0 4 13.4 GB legacy; small, very high quality loss - prefer using Q3_K_M
Mistral-Small-24B-Instruct-2501-Q4_K_M.gguf Q4_K_M 4 14.3 GB medium, balanced quality - recommended
Mistral-Small-24B-Instruct-2501-Q4_K_S.gguf Q4_K_S 4 13.5 GB small, greater quality loss
Mistral-Small-24B-Instruct-2501-Q5_0.gguf Q5_0 5 16.3 GB legacy; medium, balanced quality - prefer using Q4_K_M
Mistral-Small-24B-Instruct-2501-Q5_K_M.gguf Q5_K_M 5 16.8 GB large, very low quality loss - recommended
Mistral-Small-24B-Instruct-2501-Q5_K_S.gguf Q5_K_S 5 16.3 GB large, low quality loss - recommended
Mistral-Small-24B-Instruct-2501-Q6_K.gguf Q6_K 6 19.3 GB very large, extremely low quality loss
Mistral-Small-24B-Instruct-2501-Q8_0.gguf Q8_0 8 25.1 GB very large, extremely low quality loss - not recommended
Mistral-Small-24B-Instruct-2501-f16.gguf f16 16 47.2 GB

Quantized with llama.cpp b4595.

Downloads last month
283
GGUF
Model size
23.6B params
Architecture
llama

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Providers NEW
This model is not currently available via any of the supported third-party Inference Providers, and HF Inference API has been turned off for this model.

Model tree for second-state/Mistral-Small-24B-Instruct-2501-GGUF