NVIDIA A100 40GBBudget pickC97.3 tok/s decode
~$10,000 MSRP
Can it run?
Runs well
Using Q4_K_M in vLLM
Fit status
Runs well
Decode
26.4 tok/s
TTFT
7321 ms
Safe context
23K
Memory
24.4 GB / 34.6 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | C | Runs well | 25.6 tok/s | 10986 ms | 40K |
| Chat | C | Runs well | 25.6 tok/s | 4120 ms | 12K |
| Coding | C | Runs well | 26.4 tok/s | 7321 ms | 23K |
| RAG | C | Runs well | 25.6 tok/s | 13733 ms | 40K |
| Reasoning | C | Runs well | 25.6 tok/s | 8926 ms | 23K |
How Codestral 2 25.08 (22B params) fits at each quantization level on MacBook Pro M4 Max 48GB (34.6 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 8.6 GB | Low | D35 |
Q3_K_S | 3 | 10.8 GB | Low | D36 |
NVFP4 | 4 |
huggingface-cli download codestral-2-25.08Upgrade options
NVIDIA A100 40GBBudget pick~$10,000 MSRP
12.3 GB |
| Medium |
| D37 |
Q4_K_M | 4 | 13.4 GB | Medium | D38 |
Q5_K_M | 5 | 15.8 GB | High | D39 |
Q6_K | 6 | 18.0 GB | High | C41 |
Q8_0Best for your GPU | 8 | 23.5 GB | Very High | C44 |
F16 | 16 | 45.1 GB | Maximum | F0 |