RX 7700 XT 12GBコスパ重視
12 GB VRAM (+4)
B
Adds memory headroom for longer context windows and future model growth.65.9 tok/sデコード
Adds memory headroom for longer context windows and future model growth.
〜$449 MSRP
Can Qwen 2.5 Math 7B run on RX 5700 XT 8GB?
YES — Tight Fit
B57Good
Estimated from fit model
Qwen 2.5 Math 7B needs ~6.8 GB VRAM. RX 5700 XT 8GB has 8.0 GB. With Q4_K_M quantization, expect ~59 tok/s.
Runtime: llama.cppCapacity: TightBandwidth: LowStack: StandardBottleneck: Balanced
Operating mode
Choose the run profile you care about
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
Q4_K_M (Medium quality) — 6.8 GB, 59.2 tok/s, Tight fit
6.8 GB required8.0 GB available
85% VRAM used
Fit status
Tight fit
Decode
59.2 tok/s
TTFT
3268 ms
Safe context
4K
Memory
6.8 GB / 8.0 GB
Memory breakdown
Weights4.3 GB
KV Cache0.9 GB
Runtime0.9 GB
Headroom0.8 GB
See how fast it feels
See how fast it feelsQwen 2.5 Math 7B on RX 5700 XT 8GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.
Given information:
- Speed = 60 mph (miles per hour)
- Time = 2.5 hours
Formula: Distance = Speed x Time
Calculation:
Distance = 60 mph x 2.5 h
= 150 miles
The train travels 150 miles.
Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.
Breakdown:
- First half: 1.25 hours at 60 mph = 75 miles
- Stop: 20 minutes (no distance)
- Second half: 1.25 hours at 60 mph = 75 miles
Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph
The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 59.2 tok/s decode · 3.3s TTFT (warm) · 148 tok/s prefill
What limits this setup
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.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 59.2 tok/s | 1783 ms | 4K |
| Coding | B | Tight fit | 59.2 tok/s | 3268 ms | 4K |
| Agentic Coding | B | Runs with offload | 59.2 tok/s | 4754 ms | 4K |
| Reasoning | B | Tight fit | 59.2 tok/s | 3863 ms | 4K |
| RAG | B | Runs with offload | 59.2 tok/s | 5943 ms | 4K |
Quantization options
How Qwen 2.5 Math 7B (7B params) fits at each quantization level on RX 5700 XT 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B57 |
Q3_K_S | 3 | 3.4 GB | Low | B58 |
NVFP4 | 4 | 3.9 GB | Medium | B58 |
Q4_K_M | 4 | 4.3 GB | Medium | B57 |
Q5_K_MBest for your GPU | 5 | 5.0 GB | High | B57 |
Q6_K | 6 | 5.7 GB | High | F0 |
Q8_0 | 8 | 7.5 GB | Very High | F0 |
F16 | 16 | 14.3 GB | Maximum | F0 |
Get started
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
Qwen 2.5 Math 7Bを快適に動かすハードウェア
RX 6700 XT 12GBコスパ最良
12 GB VRAM (+4)
B
Adds memory headroom for longer context windows and future model growth.50.8 tok/sデコード
Adds memory headroom for longer context windows and future model growth.
〜$479 MSRP
RX 6750 XT 12GBAMDアップグレード
12 GB VRAM (+4)
B
Adds memory headroom for longer context windows and future model growth.58.2 tok/sデコード
Adds memory headroom for longer context windows and future model growth.
〜$549 MSRP
Frequently asked questions
Can RX 5700 XT 8GB run Qwen 2.5 Math 7B?
Yes, RX 5700 XT 8GB can run Qwen 2.5 Math 7B with a B grade (Tight fit). Expected decode speed: 59.2 tok/s.
How much VRAM does Qwen 2.5 Math 7B need?
Qwen 2.5 Math 7B (7B parameters) requires approximately 6.8 GB of memory with Q4_K_M quantization.
What is the best quantization for Qwen 2.5 Math 7B?
The recommended quantization for Qwen 2.5 Math 7B is Q4_K_M, which balances quality and memory efficiency.
What speed will Qwen 2.5 Math 7B run at on RX 5700 XT 8GB?
On RX 5700 XT 8GB, Qwen 2.5 Math 7B achieves approximately 59.2 tokens per second decode speed with a time-to-first-token of 3268ms using Q4_K_M quantization.
Can RX 5700 XT 8GB run Qwen 2.5 Math 7B for coding?
For coding workloads, Qwen 2.5 Math 7B on RX 5700 XT 8GB receives a B grade with 59.2 tok/s and 4K context.
What context window can Qwen 2.5 Math 7B use on RX 5700 XT 8GB?
On RX 5700 XT 8GB, 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.
Embed this result▼
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-5700-xt-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: