license, model_name, base_model, inference, model_creator, quantized_by

license	model_name	base_model	inference	model_creator	quantized_by
apache-2.0	Mistral-7B-Instruct-v0.3	mistralai/Mistral-7B-Instruct-v0.3	false	mistralai	Second State Inc.

---

Mistral-7B-Instruct-v0.3-GGUF

Original Model

mistralai/Mistral-7B-Instruct-v0.3

Run with LlamaEdge

• LlamaEdge version: v0.11.2

• Prompt template

  • Prompt type: mistral-instruct

  • Prompt string

    <s>[INST] {user_message_1} [/INST]{assistant_message_1}</s>[INST] {user_message_2} [/INST]{assistant_message_2}</s>
    

• Context size: 32000

• Run as LlamaEdge service

  • Chat

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Mistral-7B-Instruct-v0.3-Q5_K_M.gguf \
      llama-api-server.wasm \
      --prompt-template mistral-instruct \
      --ctx-size 32000 \
      --model-name Mistral-7B-Instruct-v0.3
    

  • Tool use

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Mistral-7B-Instruct-v0.3-Q5_K_M.gguf \
      llama-api-server.wasm \
      --prompt-template mistral-tool \
      --ctx-size 32000 \
      --model-name Mistral-7B-Instruct-v0.3
    

• Run as LlamaEdge command app

  wasmedge --dir .:. --nn-preload default:GGML:AUTO:Mistral-7B-Instruct-v0.3-Q5_K_M.gguf \
    llama-chat.wasm \
    --prompt-template mistral-instruct \
    --ctx-size 32000
  

Quantized GGUF Models

Name	Quant method	Bits	Size	Use case
Mistral-7B-Instruct-v0.3-Q2_K.gguf	Q2_K	2	2.72 GB	smallest, significant quality loss - not recommended for most purposes
Mistral-7B-Instruct-v0.3-Q3_K_L.gguf	Q3_K_L	3	3.83 GB	small, substantial quality loss
Mistral-7B-Instruct-v0.3-Q3_K_M.gguf	Q3_K_M	3	3.52 GB	very small, high quality loss
Mistral-7B-Instruct-v0.3-Q3_K_S.gguf	Q3_K_S	3	3.17 GB	very small, high quality loss
Mistral-7B-Instruct-v0.3-Q4_0.gguf	Q4_0	4	4.11 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Mistral-7B-Instruct-v0.3-Q4_K_M.gguf	Q4_K_M	4	4.37 GB	medium, balanced quality - recommended
Mistral-7B-Instruct-v0.3-Q4_K_S.gguf	Q4_K_S	4	4.14 GB	small, greater quality loss
Mistral-7B-Instruct-v0.3-Q5_0.gguf	Q5_0	5	5 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Mistral-7B-Instruct-v0.3-Q5_K_M.gguf	Q5_K_M	5	5.14 GB	large, very low quality loss - recommended
Mistral-7B-Instruct-v0.3-Q5_K_S.gguf	Q5_K_S	5	5 GB	large, low quality loss - recommended
Mistral-7B-Instruct-v0.3-Q6_K.gguf	Q6_K	6	5.95 GB	very large, extremely low quality loss
Mistral-7B-Instruct-v0.3-Q8_0.gguf	Q8_0	8	7.7 GB	very large, extremely low quality loss - not recommended
Mistral-7B-Instruct-v0.3-f16.gguf	f16	16	14.5 GB

Quantized with llama.cpp b3030.