Magistral Small 2507 needs ~27.9 GB VRAM. RTX PRO 6000 Blackwell Workstation Edition 96GB has 96.0 GB. With Q4_K_M quantization, expect ~111 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
110.5 tok/s
TTFT
1752 ms
Safe context
131K
Memory
27.9 GB / 96.0 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 | 110.5 tok/s | 955 ms | 131K |
| Coding | S | Runs well | 110.5 tok/s | 1752 ms | 131K |
| Agentic Coding | S | Runs well | 110.5 tok/s | 2548 ms | 131K |
| Reasoning | S | Runs well | 110.5 tok/s | 2070 ms | 131K |
| RAG | S | Runs well | 110.5 tok/s | 3185 ms | 131K |
How Magistral Small 2507 (24B params) fits at each quantization level on RTX PRO 6000 Blackwell Workstation Edition 96GB (96.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | A81 |
Q3_K_S | 3 | 11.8 GB | Low | A81 |
NVFP4 | 4 |
Copy-paste commands to run Magistral Small 2507 on your machine.
Run
ollama run magistralYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 123B | S | 21.8 tok/s | ||
| 30.5B |
Yes, RTX PRO 6000 Blackwell Workstation Edition 96GB can run Magistral Small 2507 with a S grade (Runs well). Expected decode speed: 110.5 tok/s.
Magistral Small 2507 (24B parameters) requires approximately 27.9 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 RTX PRO 6000 Blackwell Workstation Edition 96GB, Magistral Small 2507 achieves approximately 110.5 tokens per second decode speed with a time-to-first-token of 1752ms using Q4_K_M quantization.
For coding workloads, Magistral Small 2507 on RTX PRO 6000 Blackwell Workstation Edition 96GB receives a S grade with 110.5 tok/s and 131K context.
On RTX PRO 6000 Blackwell Workstation Edition 96GB, 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-rtx-pro-6000-blackwell-96gb" 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 |
| A81 |
Q4_K_M | 4 | 14.6 GB | Medium | A81 |
Q5_K_M | 5 | 17.3 GB | High | A82 |
Q6_K | 6 | 19.7 GB | High | A82 |
Q8_0 | 8 | 25.7 GB | Very High | A83 |
F16Best for your GPU | 16 | 49.2 GB | Maximum | S88 |
| 227.6 tok/s |
| 27B | S | 98.7 tok/s |
| 27B | S | 99 tok/s |
| 122B | S | 60.5 tok/s |