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Can the Intel Arc Pro B50 run OpenChat 3.5 (0106)?

61 ptsGood (B) · 61 of 100 points: Model quality 13.2/45, Memory fit 25.0/25, Speed 14.5/15, Memory use 8.7/15

Yes, it runs well

Runs well. At Q3_K_M it needs about 6.0 GB of 16.0 GB usable, with an estimated speed of 37.5 tok/s.

Best quant
Q3_K_M
Generation speed
37.5 tok/s
Prompt processing
1,056 tok/s
First token (1K prompt)
1.0 s
Largest safe context
8K

Download OpenChat 3.5 (0106)

Recommended for the Intel Arc Pro B50: Q3_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 openchat:7b-v3.5-0106-q3_K_M

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 Q3_K_M file (opens in a new tab)

huggingface.co/mradermacher/openchat-3.5-0106-i1-GGUF (opens in a new tab)

ollama run hf.co/mradermacher/openchat-3.5-0106-i1-GGUF:Q3_K_M

Original weights · Hugging Face

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

huggingface.co/openchat/openchat-3.5-0106 (opens in a new tab)

No sign-in needed.

Links checked 7 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.13.2 / 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.14.5 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.8.7 / 15
Total61.4 / 10061 ptsGood (B) · 61 of 100 points: Model quality 13.2/45, Memory fit 25.0/25, Speed 14.5/15, Memory use 8.7/15

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

Every quantization on the Intel Arc Pro B50

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 5.4 GB 16.0 GB 47.6 tok/s Runs well 58 ptsGood (B) · 58 of 100 points: Model quality 11.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.7/15 GGUF (opens in a new tab)
Q3_K_M 6.0 GB 16.0 GB 37.5 tok/s Runs well 61 ptsGood (B) · 61 of 100 points: Model quality 13.2/45, Memory fit 25.0/25, Speed 14.5/15, Memory use 8.7/15 GGUF (opens in a new tab)
Q4_K_M 6.9 GB 16.0 GB 29.0 tok/s Runs well 62 ptsGood (B) · 62 of 100 points: Model quality 15.0/45, Memory fit 25.0/25, Speed 12.8/15, Memory use 9.9/15 GGUF (opens in a new tab)
Q5_K_M 7.6 GB 16.0 GB 24.0 tok/s Runs well 62 ptsGood (B) · 62 of 100 points: Model quality 15.3/45, Memory fit 25.0/25, Speed 11.6/15, Memory use 11.0/15 GGUF (opens in a new tab)
Q6_K 8.4 GB 16.0 GB 20.1 tok/s Runs well 63 ptsGood (B) · 63 of 100 points: Model quality 15.6/45, Memory fit 25.0/25, Speed 10.6/15, Memory use 12.1/15 GGUF (opens in a new tab)
Q8_0 10.1 GB 16.0 GB 14.8 tok/s Runs well 64 ptsGood (B) · 64 of 100 points: Model quality 15.8/45, Memory fit 25.0/25, Speed 9.1/15, Memory use 14.6/15
F16 17.0 GB 16.0 GB 6.2 tok/s Runs with offload 46 ptsUsable (C) · 46 of 100 points: Model quality 15.8/45, Memory fit 10.0/25, Speed 5.9/15, 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.