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Can the Intel Arc A380 run Granite 4.0 H Micro?

69 ptsGood (B) · 69 of 100 points: Model quality 16.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.4/15

Yes, it runs well

Runs well. At Q5_K_M it needs about 3.2 GB of 6.0 GB usable, with an estimated speed of 45.2 tok/s.

Best quant
Q5_K_M
Generation speed
45.2 tok/s
Prompt processing
1,414 tok/s
First token (1K prompt)
0.7 s
Largest safe context
128K

Download Granite 4.0 H Micro

Recommended for the Intel Arc A380: Q5_K_M. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run granite4:micro-h

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q5_K_M file (opens in a new tab)

huggingface.co/ibm-granite/granite-4.0-h-micro-GGUF (opens in a new tab)

ollama run hf.co/ibm-granite/granite-4.0-h-micro-GGUF:Q5_K_M

Original weights · Hugging Face

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

huggingface.co/ibm-granite/granite-4.0-h-micro (opens in a new tab)

No sign-in needed.

Links checked 5 days 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.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.15.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.12.4 / 15
Total69.0 / 10069 ptsGood (B) · 69 of 100 points: Model quality 16.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.4/15

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 2.2 GB 6.0 GB 89.8 tok/s Runs well 60 ptsGood (B) · 60 of 100 points: Model quality 12.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.6/15 GGUF (opens in a new tab)
Q3_K_M 2.5 GB 6.0 GB 70.7 tok/s Runs well 64 ptsGood (B) · 64 of 100 points: Model quality 14.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.7/15 GGUF (opens in a new tab)
Q4_K_M 2.9 GB 6.0 GB 54.7 tok/s Runs well 67 ptsGood (B) · 67 of 100 points: Model quality 16.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.2/15 GGUF (opens in a new tab)
Q5_K_M 3.2 GB 6.0 GB 45.2 tok/s Runs well 69 ptsGood (B) · 69 of 100 points: Model quality 16.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.4/15 GGUF (opens in a new tab)
Q6_K 3.6 GB 6.0 GB 37.9 tok/s Runs well 70 ptsGood (B) · 70 of 100 points: Model quality 16.9/45, Memory fit 25.0/25, Speed 14.6/15, Memory use 13.8/15 GGUF (opens in a new tab)
Q8_0 4.3 GB 6.0 GB 27.8 tok/s Runs well 69 ptsGood (B) · 69 of 100 points: Model quality 17.1/45, Memory fit 25.0/25, Speed 12.5/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 7.3 GB 6.0 GB 10.4 tok/s Runs with offload 49 ptsUsable (C) · 49 of 100 points: Model quality 17.1/45, Memory fit 10.0/25, Speed 7.6/15, Memory use 15.0/15 GGUF (opens in a new tab) 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.