Can Qwen 2.5 Coder 1.5B run on Intel Arc B570 10GB?

YES — Runs Great

B63Good

Estimated from fit model

Qwen 2.5 Coder 1.5B needs ~3.2 GB VRAM. Intel Arc B570 10GB has 10.0 GB. With Q4_K_M quantization, expect ~21 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) — 3.2 GB, 21.0 tok/s, Runs well

3.2 GB required10.0 GB available

32% VRAM used

Fit status

Runs well

Decode

21.0 tok/s

TTFT

9219 ms

Safe context

33K

Memory

3.2 GB / 10.0 GB

Memory breakdown

Weights0.9 GB

KV Cache0.4 GB

Runtime0.9 GB

Headroom1.0 GB

See how fast it feels

See how fast it feelsQwen 2.5 Coder 1.5B on Intel Arc B570 10GB
1st promptCold start — includes initialization
>Write a Python function to sort a list
Here's a Python function that sorts a list using quicksort:

def quicksort(arr):
    if len(arr) <= 1:
        return arr
    pivot = arr[len(arr) // 2]
    left   = [x for x in arr if x < pivot]
    middle = [x for x in arr if x == pivot]
    right  = [x for x in arr if x > pivot]
    return quicksort(left) + middle + quicksort(right)

# Example usage
numbers = [3, 6, 8, 10, 1, 2, 1]
print(quicksort(numbers))  # [1, 1, 2, 3, 6, 8, 10]

The algorithm picks a pivot, partitions the list into smaller, equal, and larger elements, then recursively sorts each partition and concatenates the results.
2nd promptWarm — model ready, no init overhead
>Now add type hints and a docstring
def quicksort(arr: list[int]) -> list[int]:
    """Sort a list using the quicksort algorithm.

    Args:
        arr: List of integers to sort.

    Returns:
        A new sorted list.
    """
    if len(arr) <= 1:
        return arr
    pivot = arr[len(arr) // 2]
    left   = [x for x in arr if x < pivot]
    middle = [x for x in arr if x == pivot]
    right  = [x for x in arr if x > pivot]
    return quicksort(left) + middle + quicksort(right)

Added type hints for the input and return type, plus a Google-style docstring.
Estimated: 21.0 tok/s decode · 9.2s TTFT (warm) · 53 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	B	Runs well	21.0 tok/s	5029 ms	33K
Coding	B	Runs well	21.0 tok/s	9219 ms	33K
Agentic Coding	B	Runs well	21.0 tok/s	13410 ms	33K
Reasoning	B	Runs well	21.0 tok/s	10895 ms	33K
RAG	B	Runs well	21.0 tok/s	16762 ms	33K

Quantization options

How Qwen 2.5 Coder 1.5B (1.5B params) fits at each quantization level on Intel Arc B570 10GB (10.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	0.6 GB	Low	B67
Q3_K_S	3	0.7 GB	Low	B67
NVFP4	4	0.8 GB	Medium	B67
Q4_K_M	4	0.9 GB	Medium	B67
Q5_K_M	5	1.1 GB	High	B67
Q6_K	6	1.2 GB	High	B67
Q8_0	8	1.6 GB	Very High	B68
F16Best for your GPU	16	3.1 GB	Maximum	A70

Get started

Copy-paste commands to run Qwen 2.5 Coder 1.5B on your machine.

Run

ollama run qwen2.5-coder:1.5b

Opções de upgrade

Hardware que roda bem Qwen 2.5 Coder 1.5B

RTX 5070 12GBOpção econômica

12 GB VRAM (+2)672 GB/s (+292)

Raises estimated decode speed by about 36%.28.5 tok/s decodificação

Raises estimated decode speed by about 36%.

Moves you onto CUDA, which still has the broadest local-AI runtime coverage.

This is not only a hardware jump. It also gives you a cleaner runtime ecosystem for local LLM tooling.

~$549 MSRP

MacBook Pro M4 16GBMelhor custo-benefício

16 GB Unified (+6)

This setup is broadly balanced for this model.21 tok/s decodificação

~$599 MSRP

Frequently asked questions

Can Intel Arc B570 10GB run Qwen 2.5 Coder 1.5B?

Yes, Intel Arc B570 10GB can run Qwen 2.5 Coder 1.5B with a B grade (Runs well). Expected decode speed: 21.0 tok/s.

How much VRAM does Qwen 2.5 Coder 1.5B need?

Qwen 2.5 Coder 1.5B (1.5B parameters) requires approximately 3.2 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 Coder 1.5B?

The recommended quantization for Qwen 2.5 Coder 1.5B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 Coder 1.5B run at on Intel Arc B570 10GB?

On Intel Arc B570 10GB, Qwen 2.5 Coder 1.5B achieves approximately 21.0 tokens per second decode speed with a time-to-first-token of 9219ms using Q4_K_M quantization.

Can Intel Arc B570 10GB run Qwen 2.5 Coder 1.5B for coding?

For coding workloads, Qwen 2.5 Coder 1.5B on Intel Arc B570 10GB receives a B grade with 21.0 tok/s and 33K context.

What context window can Qwen 2.5 Coder 1.5B use on Intel Arc B570 10GB?

On Intel Arc B570 10GB, Qwen 2.5 Coder 1.5B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.

What should I upgrade first if Qwen 2.5 Coder 1.5B feels slow on Intel Arc B570 10GB?

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.

Would CUDA be a better path than Intel Arc B570 10GB for Qwen 2.5 Coder 1.5B?

Often yes, if your goal is the easiest setup and the widest runtime support. Intel can offer attractive memory capacity, but CUDA still tends to win on tooling maturity, guides, kernels, and model coverage for local AI.

See all results for Intel Arc B570 10GB See all hardware for Qwen 2.5 Coder 1.5B

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