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

Original Model

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

Run with Gaianet

Prompt template

prompt template: mistral-instruct

Context size

chat_ctx_size: 32000

Run with GaiaNet

• Quick start: https://docs.gaianet.ai/node-guide/quick-start

• Customize your node: https://docs.gaianet.ai/node-guide/customize

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.