Raises estimated decode speed by about 131%.
Adds memory headroom for longer context windows and future model growth.
〜$899 MSRP
Qwen 2.5 Math 7B needs ~7.6 GB VRAM. RX 7600 XT 16GB has 16.0 GB. With Q4_K_M quantization, expect ~43 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
42.5 tok/s
TTFT
4558 ms
Safe context
4K
Memory
7.6 GB / 16.0 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 | C | Runs well | 42.5 tok/s | 2486 ms | 4K |
| Coding | C | Runs well | 42.5 tok/s | 4558 ms | 4K |
| Agentic Coding | C | Runs well | 42.5 tok/s | 6630 ms | 4K |
| Reasoning | C | Runs well | 42.5 tok/s | 5387 ms | 4K |
| RAG | C | Runs well | 42.5 tok/s | 8288 ms | 4K |
How Qwen 2.5 Math 7B (7B params) fits at each quantization level on RX 7600 XT 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | C51 |
Q3_K_S | 3 | 3.4 GB | Low | C52 |
NVFP4 | 4 | 3.9 GB | Medium | C52 |
Q4_K_M | 4 | 4.3 GB | Medium | C52 |
Q5_K_M | 5 | 5.0 GB | High | C53 |
Q6_K | 6 | 5.7 GB | High | C54 |
Q8_0Best for your GPU | 8 | 7.5 GB | Very High | B56 |
F16 | 16 | 14.3 GB | Maximum | F0 |
Copy-paste commands to run Qwen 2.5 Math 7B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "Qwen/Qwen2.5-Math-7B-Instruct" \
--hf-file "Qwen2.5-Math-7B-Instruct-Q4_K_M.gguf" \
-c 4096 -ngl 99アップグレードオプション
Raises estimated decode speed by about 131%.
Adds memory headroom for longer context windows and future model growth.
〜$899 MSRP
Raises estimated decode speed by about 68%.
Adds memory headroom for longer context windows and future model growth.
〜$1,250 MSRP
Yes, RX 7600 XT 16GB can run Qwen 2.5 Math 7B with a C grade (Runs well). Expected decode speed: 42.5 tok/s.
Qwen 2.5 Math 7B (7B parameters) requires approximately 7.6 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 2.5 Math 7B is Q4_K_M, which balances quality and memory efficiency.
On RX 7600 XT 16GB, Qwen 2.5 Math 7B achieves approximately 42.5 tokens per second decode speed with a time-to-first-token of 4558ms using Q4_K_M quantization.
For coding workloads, Qwen 2.5 Math 7B on RX 7600 XT 16GB receives a C grade with 42.5 tok/s and 4K context.
On RX 7600 XT 16GB, Qwen 2.5 Math 7B can safely use up to 4K tokens of context. The model's official context limit is 4K, 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/qwen-2.5-math-7b-on-rx-7600-xt-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: