Mistral AI
Ministral 3 8B
small machinesvision
8,9B
Parameters
4,8 Go
Q4_K_M file
≥ 6,3 Go
Recommended VRAM
262 144
Max context
Speed by graphics card
Simulate in the “Configurator” →Standard llama-bench run (prompt 512 / generation 128 tokens), model fully in VRAM. Click a card for details. Electricity cost at the default price (0,25 €/kWh).
| Card · Q4_K_M | VRAM | Generation | Prompt | VRAM used | Power | € elec. / M tok | Price |
|---|---|---|---|---|---|---|---|
| RTX 4070 Ti | 12 Go | 84,0 tok/s | 5 555 | 5,6 Go | 149 W | 0,12 €/M tok | — |
Not measured on these cards yet — click for an estimate:
Technical sheet
- Published
- 2025-10-31
- Architecture
- 34 layers · 8 KV heads · dimension 128
- Attention
- Standard: every layer keeps the whole context in memory.
- Context cache (f16)
- ≈ 133 MB per 1,000 tokens · 4,3 Go for 32,768 tokens
- GGUF file
- bartowski/mistralai_Ministral-3-8B-Instruct-2512-GGUF · mistralai_Ministral-3-8B-Instruct-2512-Q4_K_M.gguf Download (4,8 Go)
- Official repo
- mistralai/Ministral-3-8B-Instruct-2512
Public Hugging Face data (official config.json, GGUF repo). The context cache only counts full-attention layers.