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Ministral 3 8B Instruct
Model family: ministral-3
Balanced mid-size Ministral 3 — 8B parameters with vision, multilingual, 256K context. Fits in 12GB VRAMThe memory built into a GPU. VRAM size determines what models you can load and run — a model's weights must fit in VRAM (or be cleverly swapped in and out). A 7B model in 4-bit quantization needs about 6GB of VRAM; a 70B model in 4-bit needs about 40GB; full-precision frontier models need multiple high-end GPUs. When people talk about a model "fitting" on a GPU, they mean VRAM. in FP8. Apache 2.0.
Identity
- Creator
- Mistral AI
- Model family
- ministral-3
- Release date
- 2025-12-01
Technical specs
- Parameter count
- 8B
- Context window
- 262K tokens
- Modalities
- Image Input
- Text
- Primary capabilities
- Chat
- Function Calling
- Instruction Following
- Long Context
- Multilingual
- Tool Use
- Vision
License
- License
- Apache 2.0
- Commercial use
- Allowed
- Terms
- Modification ✓
- Redistribution ✓
- Attribution ✓
Access
- Openness
- Open Weight
- Access methods
- Api First Party
- Local Runtime Llama Cpp
- Local Runtime Lm Studio
- Local Runtime Ollama
- Local Runtime Vllm
- Weights Download Direct
- Weights Download Hf
- Cost tier
- Mixed
- llm
- open-weight
- commercial-friendly
- small-to-mid
- long-context
- multimodal
- multilingual
- edge
- laptop-friendly
- apache-licensed
- eu-based
- vision