MacBook Pro M4 Max 48GBBudget pick
48 GB Unified (+16)
C
This setup is broadly balanced for this model.95.3 tok/s decode
~$2,499 MSRP
Qwen 2.5 Math 7B needs ~9.2 GB VRAM. Radeon AI PRO R9700 32GB has 32.0 GB. With Q4_K_M quantization, expect ~96 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
96.0 tok/s
TTFT
2016 ms
Safe context
4K
Memory
9.2 GB / 32.0 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 | 96.0 tok/s | 1100 ms | 4K |
| Coding | C | Runs well | 96.0 tok/s | 2016 ms | 4K |
| Agentic Coding | C | Runs well | 96.0 tok/s | 2933 ms | 4K |
| Reasoning | C | Runs well | 96.0 tok/s | 2383 ms | 4K |
| RAG | C | Runs well | 96.0 tok/s | 3666 ms | 4K |
How Qwen 2.5 Math 7B (7B params) fits at each quantization level on Radeon AI PRO R9700 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | C47 |
Q3_K_S | 3 | 3.4 GB | Low | C47 |
NVFP4 | 4 | 3.9 GB | Medium | C48 |
Q4_K_M | 4 | 4.3 GB | Medium | C48 |
Q5_K_M | 5 | 5.0 GB | High | C48 |
Q6_K | 6 | 5.7 GB | High | C48 |
Q8_0 | 8 | 7.5 GB | Very High | C49 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | C52 |
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 99Upgrade options
Yes, Radeon AI PRO R9700 32GB can run Qwen 2.5 Math 7B with a C grade (Runs well). Expected decode speed: 96.0 tok/s.
Qwen 2.5 Math 7B (7B parameters) requires approximately 9.2 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 Radeon AI PRO R9700 32GB, Qwen 2.5 Math 7B achieves approximately 96.0 tokens per second decode speed with a time-to-first-token of 2016ms using Q4_K_M quantization.
For coding workloads, Qwen 2.5 Math 7B on Radeon AI PRO R9700 32GB receives a C grade with 96.0 tok/s and 4K context.
On Radeon AI PRO R9700 32GB, 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-radeon-ai-pro-r9700-32gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: