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Can the Intel Arc A380 run Aya Vision 8B?

67 ptsGood (B) · 67 of 100 points: Model quality 16.6/45, Memory fit 24.0/25, Speed 12.1/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q3_K_M it needs about 5.5 GB of 6.0 GB usable, with an estimated speed of 26.1 tok/s.

Best quant
Q3_K_M
Generation speed
26.1 tok/s
Prompt processing
523 tok/s
First token (1K prompt)
2.0 s
Largest safe context
16K

Download Aya Vision 8B

Original weights · Hugging Face

Full-precision files from Cohere, for fine-tuning, vLLM, Transformers.

huggingface.co/CohereLabs/aya-vision-8b (opens in a new tab)

Free Hugging Face account needed: accept the license on the model page and the download starts right away.

Links checked 1 week ago against Hugging Face, Ollama and GitHub.

How the B grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.16.6 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.24.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.12.1 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.15.0 / 15
Total67.8 / 10067 ptsGood (B) · 67 of 100 points: Model quality 16.6/45, Memory fit 24.0/25, Speed 12.1/15, Memory use 15.0/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the Intel Arc A380

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 4.7 GB 6.0 GB 33.2 tok/s Runs well 67 ptsGood (B) · 67 of 100 points: Model quality 13.9/45, Memory fit 25.0/25, Speed 13.7/15, Memory use 15.0/15 All files (opens in a new tab)
Q3_K_M 5.5 GB 6.0 GB 26.1 tok/s Tight fit 67 ptsGood (B) · 67 of 100 points: Model quality 16.6/45, Memory fit 24.0/25, Speed 12.1/15, Memory use 15.0/15 All files (opens in a new tab)
Q4_K_M 6.5 GB 6.0 GB 18.1 tok/s Runs with offload 53 ptsUsable (C) · 53 of 100 points: Model quality 18.8/45, Memory fit 10.0/25, Speed 10.1/15, Memory use 15.0/15 All files (opens in a new tab)
Q5_K_M 7.4 GB 6.0 GB 13.3 tok/s Runs with offload 52 ptsUsable (C) · 52 of 100 points: Model quality 19.2/45, Memory fit 10.0/25, Speed 8.6/15, Memory use 15.0/15 All files (opens in a new tab)
Q6_K 8.3 GB 6.0 GB 10.2 tok/s Heavy offload 46 ptsUsable (C) · 46 of 100 points: Model quality 19.6/45, Memory fit 4.0/25, Speed 7.6/15, Memory use 15.0/15 All files (opens in a new tab)
Q8_0 10.4 GB 6.0 GB 6.7 tok/s Heavy offload 44 ptsUsable (C) · 44 of 100 points: Model quality 19.8/45, Memory fit 4.0/25, Speed 6.1/15, Memory use 15.0/15 All files (opens in a new tab)
F16 18.5 GB 6.0 GB 2.6 tok/s Heavy offload 42 ptsUsable (C) · 42 of 100 points: Model quality 19.8/45, Memory fit 4.0/25, Speed 3.8/15, Memory use 15.0/15 Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.