Check my GPU

on

Can the Intel Core Ultra 200H (Arc 140T) (96 GB) run Qwen3 Coder Next (80B-A3B)?

85 ptsExcellent (S) · 85 of 100 points: Model quality 36.8/45, Memory fit 24.0/25, Speed 9.5/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q4_K_M it needs about 53.8 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
45K

Download Qwen3 Coder Next (80B-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.

Quickest · Ollama

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

ollama run qwen3-coder-next:q4_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 Q4_K_M files (opens in a new tab)

huggingface.co/Qwen/Qwen3-Coder-Next-GGUF (opens in a new tab)

ollama run hf.co/Qwen/Qwen3-Coder-Next-GGUF

Original weights · Hugging Face

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

huggingface.co/Qwen/Qwen3-Coder-Next (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Alibaba. The weights themselves download from Hugging Face.

github.com/QwenLM/Qwen3-Coder (opens in a new tab)

git clone https://github.com/QwenLM/Qwen3-Coder

Qwen’s coder repo, renamed from Qwen2.5-Coder to Qwen3-Coder.

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

How the S 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.36.8 / 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.9.5 / 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
Total85.3 / 10085 ptsExcellent (S) · 85 of 100 points: Model quality 36.8/45, Memory fit 24.0/25, Speed 9.5/15, 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 Core Ultra 200H (Arc 140T) (96 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 37.0 GB 54.7 GB 26.3 tok/s Runs well 79 ptsGreat (A) · 79 of 100 points: Model quality 27.1/45, Memory fit 25.0/25, Speed 12.2/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q3_K_M 44.2 GB 54.7 GB 20.7 tok/s Runs well 83 ptsGreat (A) · 83 of 100 points: Model quality 32.5/45, Memory fit 25.0/25, Speed 10.8/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q4_K_M 53.8 GB 54.7 GB 16.0 tok/s Tight fit 85 ptsExcellent (S) · 85 of 100 points: Model quality 36.8/45, Memory fit 24.0/25, Speed 9.5/15, Memory use 15.0/15 GGUF · folder (opens in a new tab)
Q5_K_M 61.7 GB 54.7 GB 11.2 tok/s Heavy offload 64 ptsGood (B) · 64 of 100 points: Model quality 37.5/45, Memory fit 4.0/25, Speed 8.0/15, Memory use 15.0/15 GGUF · folder (opens in a new tab)
Q6_K 70.5 GB 54.7 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.5/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
Q8_0 89.6 GB 54.7 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.6/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
F16 165 GB 54.7 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.6/45, 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.