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Run LLM Locally

Qwen3 4B on the Arc A770 16 GB

With 16 GB of VRAM, the Arc A770 16 GB runs Qwen3 4B at Q4_K_M entirely on the GPU with an 8K context (about 4.6 GB needed). At Q8_0 it fits entirely.

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Qwen3 4B

Q4_K_M · 8K context

Excellent

The model needs about 4.6 GB and fits in the 15.5 GB available, with 10.9 GB to spare.

Your hardware
Arc A770 16 GB · 64 GB RAM
Estimated memory
~4.6 GB estimate
VRAM (usable memory)
15.5 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
68–107 tok/s estimate
Largest context in fast memory
82K tokens
Confidence: low

Based on: memory bandwidth (560 GB/s) and model size

Memory breakdown

~4.6 GB (4.2 GB–5 GB) needed · estimate

Fits entirely in VRAM · 10.9 GB left

  • Model weights2.3 GB
  • KV cache1.1 GB
  • Runtime overhead0.8 GB
  • Safety margin0.3 GB
Assumptions: context 8K tokens · KV cache f16 · llama.cpp (SYCL) · flash attention on · weights = real file size

EstimateData updated 24 days agoSource: Run LLM Locally engine, Hugging Face config.json + model card

What makes this estimate less reliable

  • no benchmark for this hardware and model yet

Other quantizations on the Arc A770 16 GB

Qwen3 4B on Arc A770 16 GB + 64 GB RAM · 8K context
Qwen3 4B Q8_08K~6.2 GB · 43–68 tok/s estimateExcellent
Qwen3 4B Q6_K8K~5.3 GB · 54–85 tok/s estimateExcellent
Qwen3 4B Q5_K_M8K~4.9 GB · 60–95 tok/s estimateExcellent
Qwen3 4B Q4_K_M8K~4.6 GB · 68–107 tok/s estimateExcellent
Qwen3 4B IQ4_XS8K~4.4 GB · 73–115 tok/s estimateExcellent
Qwen3 4B Q3_K_M8K~4.2 GB · 79–123 tok/s estimateExcellent

Alternatives

GPUs that run Qwen3 4B Q4_K_M entirely in VRAM

Other models that fit the Arc A770 16 GB

Where to buy a Arc A770 16 GB

Prices and links follow the market you choose.

Intel Arc A770 16 GB

16 GB GDDR6 · 560 GB/s · 225 W

ExcellentRuns Qwen3 4B Q4_K_M entirely in memory

Price not available

Availability unknown

View on amazon.com

Affiliate link

No current offer imported for this market: the link opens a marketplace search.

Frequently asked questions

Can the Arc A770 16 GB run Qwen3 4B?
The model needs about 4.6 GB and fits in the 15.5 GB available, with 10.9 GB to spare.
Which quantization should I use on the Arc A770 16 GB?
Q8_0 is the highest-precision quantization that fits entirely in VRAM at 8K context. ~6.2 GB / 15.5 GB.
What is the largest context on the Arc A770 16 GB?
At Q4_K_M, about 82K tokens fit entirely in VRAM with an f16 KV cache. A q8_0 KV cache roughly doubles that.
How fast is Qwen3 4B (Arc A770 16 GB)?
We estimate 68–107 tok/s (estimate, confidence low). Based on: memory bandwidth (560 GB/s) and model size.