Can WizardMath 7B run on Intel Arc B570 10GB?

YES — Runs Great

A76Great

○Estimated from fit model

WizardMath 7B needs ~8.1 GB VRAM. Intel Arc B570 10GB has 10.0 GB. With Q4_K_M quantization, expect ~52 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: 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.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 8.1 GB, 51.7 tok/s, Runs well

8.1 GB required10.0 GB available

81% VRAM used

Fit status

Runs well

Decode

51.7 tok/s

TTFT

3748 ms

Safe context

Memory

8.1 GB / 10.0 GB

Memory breakdown

Weights4.3 GB

KV Cache2.0 GB

Runtime0.9 GB

Headroom1.0 GB

See how fast it feels

See how fast it feelsWizardMath 7B on Intel Arc B570 10GB
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: 51.7 tok/s decode · 3.7s TTFT (warm) · 129 tok/s prefill

What limits this setup

The raw memory story may look fine, but the software ecosystem is still a constraint here.

Runtime ecosystem is narrower than CUDA

Intel GPUs can look attractive on memory per dollar, but local AI tooling, kernels, and model coverage are still broader and easier on CUDA today.

Best improvement path

Prefer CUDA if you want the path of least resistance

If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs well	51.7 tok/s	2044 ms	4K
Coding	A	Runs well	51.7 tok/s	3748 ms	4K
Agentic Coding	A	Runs with offload (needs ~0 GB host RAM)	38.9 tok/s	7240 ms	4K
Reasoning	A	Runs well	51.7 tok/s	4429 ms	4K
RAG	A	Runs with offload (needs ~0 GB host RAM)	38.9 tok/s	9049 ms	4K

Quantization options

How WizardMath 7B (7B params) fits at each quantization level on Intel Arc B570 10GB (10.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	A71
Q3_K_S	3	3.4 GB	Low	A72
NVFP4	4	3.9 GB	Medium	A73
Q4_K_M	4	4.3 GB	Medium	A74
Q5_K_M	5	5.0 GB	High	A73
Q6_KBest for your GPU	6	5.7 GB	High	A73
Q8_0	8	7.5 GB	Very High	F0
F16	16	14.3 GB	Maximum	F0

Get started

Copy-paste commands to run WizardMath 7B on your machine.

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
 --hf-repo "WizardLMTeam/WizardMath-7B-V1.1" \
 --hf-file "WizardMath-7B-V1.1-Q4_K_M.gguf" \
 -c 4096 -ngl 99

Your hardware

More models your Intel Arc B570 10GB can run

Model	Params	Grade	Decode
👁 Alibaba Qwen 3.5 9B	9B	S	40.2 tok/s
👁 Alibaba Qwen 3 8B	8B	S	45.2 tok/s
👁 NVIDIA Nemotron Nano 8B	8B	S	45.2 tok/s
👁 InternLM InternVL2 8B	8B	A	45.2 tok/s
👁 Mistral Ministral 3 8B	8B	A	45.2 tok/s

Frequently asked questions

See all results for Intel Arc B570 10GB See all hardware for WizardMath 7B

URL: https://willitrunai.com/can-run/wizard-math-7b-on-arc-b570-10gb

⇱ WizardMath 7B on Intel Arc B570 10GB? YES