Magistral Small 2507 needs ~23.1 GB VRAM. NVIDIA A40 48GB has 48.0 GB. With Q4_K_M quantization, expect ~40 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
39.9 tok/s
TTFT
4857 ms
Safe context
131K
Memory
23.1 GB / 48.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs well | 39.9 tok/s | 2649 ms | 131K |
| Coding | S | Runs well | 39.9 tok/s | 4857 ms | 131K |
| Agentic Coding | S | Runs well | 39.9 tok/s | 7064 ms | 131K |
| Reasoning | S | Runs well | 39.9 tok/s | 5740 ms | 131K |
| RAG | S | Runs well | 39.9 tok/s | 8830 ms | 131K |
How Magistral Small 2507 (24B params) fits at each quantization level on NVIDIA A40 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | A84 |
Q3_K_S | 3 | 11.8 GB | Low | A85 |
NVFP4 | 4 |
Copy-paste commands to run Magistral Small 2507 on your machine.
Run
ollama run magistralYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | S | 82.1 tok/s | ||
| 27B | S | 35.6 tok/s |
Yes, NVIDIA A40 48GB can run Magistral Small 2507 with a S grade (Runs well). Expected decode speed: 39.9 tok/s.
Magistral Small 2507 (24B parameters) requires approximately 23.1 GB of memory with Q4_K_M quantization.
The recommended quantization for Magistral Small 2507 is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA A40 48GB, Magistral Small 2507 achieves approximately 39.9 tokens per second decode speed with a time-to-first-token of 4857ms using Q4_K_M quantization.
For coding workloads, Magistral Small 2507 on NVIDIA A40 48GB receives a S grade with 39.9 tok/s and 131K context.
On NVIDIA A40 48GB, Magistral Small 2507 can safely use up to 131K tokens of context. The model's official context limit is 131K, 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/magistral-small-2507-on-a40-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
13.4 GB |
| Medium |
| S85 |
Q4_K_M | 4 | 14.6 GB | Medium | S86 |
Q5_K_M | 5 | 17.3 GB | High | S87 |
Q6_K | 6 | 19.7 GB | High | S87 |
Q8_0Best for your GPU | 8 | 25.7 GB | Very High | S90 |
F16 | 16 | 49.2 GB | Maximum | F0 |
| 27B | S | 35.7 tok/s |
| 35B | S | 69 tok/s |
| 30B | S | 84.9 tok/s |