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Can the Intel Core Ultra 200H (Arc 140T) (96 GB) run Qwen AgentWorld 35B-A3B?

82 ptsGreat (A) · 82 of 100 points: Model quality 37.2/45, Memory fit 25.0/25, Speed 9.5/15, Memory use 11.1/15

Yes, it runs well

Runs well. At Q4_K_M it needs about 26.3 GB of 54.7 GB usable, with an estimated speed of 16.0 tok/s.

Best quant
Q4_K_M
Generation speed
16.0 tok/s
Prompt processing
1,687 tok/s
First token (1K prompt)
0.6 s
Largest safe context
256K

Download Qwen AgentWorld 35B-A3B

Recommended for the Intel Core Ultra 200H (Arc 140T) (96 GB): Q4_K_M. Every other quantization has its own download link in the table below.

Quantized files · GGUF

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

Download the Q4_K_M file (opens in a new tab)

huggingface.co/unsloth/Qwen-AgentWorld-35B-A3B-GGUF (opens in a new tab)

ollama run hf.co/unsloth/Qwen-AgentWorld-35B-A3B-GGUF:Q4_K_M

Original weights · Hugging Face

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

huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B (opens in a new tab)

No sign-in needed.

Links checked 5 days ago against Hugging Face, Ollama and GitHub.

How the A 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.37.2 / 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.9.5 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.11.1 / 15
Total82.8 / 10082 ptsGreat (A) · 82 of 100 points: Model quality 37.2/45, Memory fit 25.0/25, Speed 9.5/15, Memory use 11.1/15

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

Every quantization on the Intel Core Ultra 200H (Arc 140T) (96 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 19.0 GB 54.7 GB 26.3 tok/s Runs well 72 ptsGreat (A) · 72 of 100 points: Model quality 27.4/45, Memory fit 25.0/25, Speed 12.2/15, Memory use 8.0/15 GGUF (UD-Q2_K_XL) (opens in a new tab)
Q3_K_M 22.1 GB 54.7 GB 20.7 tok/s Runs well 78 ptsGreat (A) · 78 of 100 points: Model quality 32.9/45, Memory fit 25.0/25, Speed 10.8/15, Memory use 9.3/15 GGUF (opens in a new tab)
Q4_K_M 26.3 GB 54.7 GB 16.0 tok/s Runs well 82 ptsGreat (A) · 82 of 100 points: Model quality 37.2/45, Memory fit 25.0/25, Speed 9.5/15, Memory use 11.1/15 GGUF (opens in a new tab)
Q5_K_M 29.8 GB 54.7 GB 13.2 tok/s Runs well 84 ptsGreat (A) · 84 of 100 points: Model quality 38.0/45, Memory fit 25.0/25, Speed 8.6/15, Memory use 12.5/15 GGUF (opens in a new tab)
Q6_K 33.6 GB 54.7 GB 11.1 tok/s Runs well 85 ptsExcellent (S) · 85 of 100 points: Model quality 38.8/45, Memory fit 25.0/25, Speed 7.9/15, Memory use 14.2/15 GGUF (opens in a new tab)
Q8_0 41.9 GB 54.7 GB 8.1 tok/s Runs well 85 ptsExcellent (S) · 85 of 100 points: Model quality 39.2/45, Memory fit 25.0/25, Speed 6.8/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 74.5 GB 54.7 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.7/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (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.