Magistral Small 2507 needs ~20.4 GB VRAM. RX 7900 XTX 24GB has 24.0 GB. With Q4_K_M quantization, expect ~51 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
Tight fit
Decode
50.8 tok/s
TTFT
3814 ms
Safe context
40K
Memory
20.4 GB / 24.0 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 | 50.8 tok/s | 2081 ms | 40K |
| Coding | S | Tight fit | 50.8 tok/s | 3814 ms | 40K |
| Agentic Coding | S | Runs with offload | 50.8 tok/s | 5548 ms | 40K |
| Reasoning | S | Tight fit | 50.8 tok/s | 4508 ms | 40K |
| RAG | S | Runs with offload | 50.8 tok/s | 6935 ms | 40K |
How Magistral Small 2507 (24B params) fits at each quantization level on RX 7900 XTX 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | S90 |
Q3_K_S | 3 | 11.8 GB | Low | S92 |
NVFP4 | 4 | 13.4 GB | Medium | S92 |
Q4_K_M | 4 | 14.6 GB | Medium | S91 |
Q5_K_MBest for your GPU | 5 | 17.3 GB | High | S91 |
Q6_K | 6 | 19.7 GB | High | F0 |
Q8_0 | 8 | 25.7 GB | Very High | F0 |
F16 | 16 | 49.2 GB | Maximum | F0 |
Copy-paste commands to run Magistral Small 2507 on your machine.
Run
ollama run magistralYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen3-Coder 30B A3B Instruct | 30.5B | S | 104.5 tok/s | |
| Qwen 3.5 27B | 27B | S | 45.3 tok/s | |
| Qwen 3.6 27B | 27B | S | 29.8 tok/s | |
| Qwen 3.6 35B A3B | 35B | A | 45 tok/s | |
| Qwen3-VL 30B A3B Instruct | 30B | S | 108.1 tok/s |
Yes, RX 7900 XTX 24GB can run Magistral Small 2507 with a S grade (Tight fit). Expected decode speed: 50.8 tok/s.
Magistral Small 2507 (24B parameters) requires approximately 20.4 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 RX 7900 XTX 24GB, Magistral Small 2507 achieves approximately 50.8 tokens per second decode speed with a time-to-first-token of 3814ms using Q4_K_M quantization.
For coding workloads, Magistral Small 2507 on RX 7900 XTX 24GB receives a S grade with 50.8 tok/s and 40K context.
On RX 7900 XTX 24GB, Magistral Small 2507 can safely use up to 40K 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-rx-7900-xtx-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: