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URL: https://willitrunai.com/can-run/qwen-2.5-math-7b-on-rx-7600m-8gb


Can Qwen 2.5 Math 7B run on Radeon RX 7600M 8GB?

YES — Tight Fit

B55Good
Estimated from fit model

Qwen 2.5 Math 7B needs ~6.8 GB VRAM. Radeon RX 7600M 8GB has 8.0 GB. With Q4_K_M quantization, expect ~40 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: LowStack: StandardBottleneck: Balanced
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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.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 6.8 GB, 43.2 tok/s, Tight fit
6.8 GB required8.0 GB available
85% VRAM used

Fit status

Tight fit

Decode

43.2 tok/s

TTFT

4481 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 Radeon RX 7600M 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: 43.2 tok/s decode · 4.5s TTFT (warm) · 108 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

WorkloadGradeFitDecodeTTFTContext
ChatBRuns well39.8 tok/s2654 ms4K
CodingBTight fit39.8 tok/s4865 ms4K
Agentic CodingBRuns with offload39.8 tok/s7076 ms4K
ReasoningBTight fit39.8 tok/s5750 ms4K
RAGBRuns with offload39.8 tok/s8846 ms4K

Quantization options

How Qwen 2.5 Math 7B (7B params) fits at each quantization level on Radeon RX 7600M 8GB (8.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
2.7 GB
LowB57
Q3_K_S
3
3.4 GB
LowB58
NVFP4
4

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

Upgrade options

Hardware that runs Qwen 2.5 Math 7B well

RX 7700 XT 12GBBudget pick
12 GB VRAM (+4)432 GB/s (+144)
B
Raises estimated decode speed by about 53%.65.9 tok/s decode

Raises estimated decode speed by about 53%.

Adds memory headroom for longer context windows and future model growth.

~$449 MSRP

RX 6700 XT 12GBBest value
12 GB VRAM (+4)384 GB/s (+96)
B
Adds memory headroom for longer context windows and future model growth.50.8 tok/s decode

Adds memory headroom for longer context windows and future model growth.

~$479 MSRP

RX 9070 16GBAMD upgrade
16 GB VRAM (+8)640 GB/s (+352)
B
Raises estimated decode speed by about 127%.98 tok/s decode

Raises estimated decode speed by about 127%.

Adds memory headroom for longer context windows and future model growth.

~$479 MSRP

Frequently asked questions

See all results for Radeon RX 7600M 8GBSee all hardware for Qwen 2.5 Math 7B
3.9 GB
Medium
B58
Q4_K_M
4
4.3 GB
MediumB57
Q5_K_MBest for your GPU
5
5.0 GB
HighB57
Q6_K
6
5.7 GB
HighF0
Q8_0
8
7.5 GB
Very HighF0
F16
16
14.3 GB
MaximumF0