Codestral 2 25.08 needs ~19.2 GB VRAM. Tesla P40 24GB has 24.0 GB. With Q4_K_M quantization, expect ~15 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
14.6 tok/s
TTFT
13258 ms
Safe context
48K
Memory
19.2 GB / 24.0 GB
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs well | 14.6 tok/s | 7232 ms | 48K |
| Coding | S | Runs well | 14.6 tok/s | 13258 ms | 48K |
| Agentic Coding | A | Tight fit | 14.6 tok/s | 19284 ms | 48K |
| Reasoning | S | Runs well | 14.6 tok/s | 15668 ms | 48K |
| RAG | A | Tight fit | 14.6 tok/s | 24105 ms | 48K |
How Codestral 2 25.08 (22B params) fits at each quantization level on Tesla P40 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 8.6 GB | Low | A82 |
Q3_K_S | 3 | 10.8 GB | Low | A84 |
NVFP4 | 4 |
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 |
|---|---|---|---|---|
| 30.5B | S | 30.9 tok/s | ||
| 27B | S | 13.4 tok/s |
Yes, Tesla P40 24GB can run Codestral 2 25.08 with a S grade (Runs well). Expected decode speed: 14.6 tok/s.
Codestral 2 25.08 (22B parameters) requires approximately 19.2 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 Tesla P40 24GB, Codestral 2 25.08 achieves approximately 14.6 tokens per second decode speed with a time-to-first-token of 13258ms using Q4_K_M quantization.
For coding workloads, Codestral 2 25.08 on Tesla P40 24GB receives a S grade with 14.6 tok/s and 48K context.
On Tesla P40 24GB, Codestral 2 25.08 can safely use up to 48K tokens of context. The model's official context limit is 256K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/codestral-2-25.08-on-tesla-p40-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
12.3 GB |
| Medium |
| A85 |
Q4_K_M | 4 | 13.4 GB | Medium | A84 |
Q5_K_M | 5 | 15.8 GB | High | A84 |
Q6_KBest for your GPU | 6 | 18.0 GB | High | A84 |
Q8_0 | 8 | 23.5 GB | Very High | F0 |
F16 | 16 | 45.1 GB | Maximum | F0 |
| 27B | S | 10.2 tok/s |
| 35B | A | 12.7 tok/s |
| 30B | S | 31.9 tok/s |