Yes — Ministral 8B (8B) runs at 72 tok/s on M4 with 16 GB RAM using Q4_K_M quantization via MLX. First token latency is 0.5s. Mistral's 8B model optimized for edge inference with strong instruction following.
Want to run Ministral 8B faster — or step up to bigger models? Find your Mac →The LLMCheck index estimates Ministral 8B on M4 using our published methodology: Q4_K_M quantization, memory-bandwidth scaling, and cross-referenced third-party benchmarks where available. Figures are transparent estimates — own this config? Submit a real benchmark →
| Metric | Value |
|---|---|
| Tokens per second | 72 tok/s |
| Time to first token | 0.5s |
| Quantization | Q4_K_M |
| Minimum RAM | 16 GB |
| Recommended engine | MLX |
| Parameters | 8B |
| Benchmark date | 2026-02 |
Q4_K_M 8B MLX M4
The recommended engine for Ministral 8B on M4 is MLX. Install with pip and pull the model:
Alternatively, you can use Ollama for a simpler setup:
| Chip | Speed | First Token | Min RAM | Engine |
|---|---|---|---|---|
| M5 Max | 98 tok/s | 0.4s | 64 GB | Ollama |
| M3 | 55 tok/s | 0.7s | 16 GB | LM Studio |
To run Ministral 8B on M4 you need:
Ministral 8B needs about 16 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
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See how Ministral 8B stacks up against other models on your specific Mac hardware.
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