Mistral 7B Instruct
Well-rounded 7B instruct model from Mistral AI. Good general-purpose default.
At a glance
- Parameters
- 7B
- Quantization
- Q4_K_M
- Context window
- 33K tokens
- Approx. size
- 4.4 GB
- Engines
- llama.cpp, MLX, Ollama
- License
- Apache-2.0 (open)
- Version
- v1.1.0 , released 2026-04-26
- Family
- mistral
Tuning
Defaults a gezel client applies out of the box, from real evaluation runs against this exact quantization.
- sampling.temperature
0.7- sampling.topP
0.95- sampling.maxTokens
8192- sampling.repetitionPenalty
1.1- sampling.repetitionContext
20
Model behaviors
Client-side behavior modules the catalog enables for this model (reasoning-tag handling, fabrication detection, prompt shaping).
- fabrication.detect-past-tense-no-tools
- fabrication.detect-claim-without-tool
- prompt.tool-cookbook-condensed
- turn.preamble-folding
- turn.ramble-detection
- provider.flatten-tool-transcript
- mcp.compact-tool-schemas
Sources
- llama.cpp (GGUF)
- bartowski/Mistral-7B-Instruct-v0.3-GGUF ·
Mistral-7B-Instruct-v0.3-Q4_K_M.gguf· Q4_K_M - MLX
- mlx-community/Mistral-7B-Instruct-v0.3-4bit
- Ollama
mistral:7b- Upstream
- https://ollama.com/library/mistral
- Manifest
- View on GitHub
Tags
- mistral
- tools