Codestral 2 25.08 needs ~23.7 GB VRAM. MacBook Pro M4 Pro 64GB has 46.1 GB. With Q4_K_M quantization, expect ~22 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
22.2 tok/s
TTFT
8737 ms
Safe context
163K
Memory
23.7 GB / 46.1 GB
This setup is broadly balanced for this model.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 22.2 tok/s | 4765 ms | 163K |
| Coding | A | Runs well | 22.2 tok/s | 8737 ms | 163K |
| Agentic Coding | A | Runs well | 22.2 tok/s | 12708 ms | 163K |
| Reasoning | A | Runs well | 22.2 tok/s | 10325 ms | 163K |
| RAG | A | Runs well | 22.2 tok/s | 15885 ms | 163K |
How Codestral 2 25.08 (22B params) fits at each quantization level on MacBook Pro M4 Pro 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 8.6 GB | Low | A77 |
Q3_K_S | 3 | 10.8 GB | Low | A78 |
NVFP4 | 4 | 12.3 GB | Medium | A78 |
Q4_K_M | 4 | 13.4 GB | Medium | A78 |
Q5_K_M | 5 | 15.8 GB | High | A79 |
Q6_K | 6 | 18.0 GB | High | A80 |
Q8_0Best for your GPU | 8 | 23.5 GB | Very High | A82 |
F16 | 16 | 45.1 GB | Maximum | F0 |
Copy-paste commands to run Codestral 2 25.08 on your machine.
Run
lms load codestral-2508 && lms server startYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen3-Coder 30B A3B Instruct | 30.5B | S | 31.8 tok/s | |
| Qwen 3.5 27B | 27B | S | 22.7 tok/s | |
| Qwen 3.6 27B | 27B | S | 17.3 tok/s | |
| Qwen 3.6 35B A3B | 35B | S | 29.4 tok/s | |
| Qwen3-VL 30B A3B Instruct | 30B | S | 32.9 tok/s |
Yes, MacBook Pro M4 Pro 64GB can run Codestral 2 25.08 with a A grade (Runs well). Expected decode speed: 22.2 tok/s.
Codestral 2 25.08 (22B parameters) requires approximately 23.7 GB of memory with Q4_K_M quantization.
The recommended quantization for Codestral 2 25.08 is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M4 Pro 64GB, Codestral 2 25.08 achieves approximately 22.2 tokens per second decode speed with a time-to-first-token of 8737ms using Q4_K_M quantization.
For coding workloads, Codestral 2 25.08 on MacBook Pro M4 Pro 64GB receives a A grade with 22.2 tok/s and 163K context.
On MacBook Pro M4 Pro 64GB, Codestral 2 25.08 can safely use up to 163K tokens of context. The model's official context limit is 256K, but available memory constrains the safe maximum.
Not always. MacBook Pro M4 Pro 64GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/codestral-2-25.08-on-m4-pro-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: