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Can the NVIDIA GeForce RTX 4070 SUPER run Qwen3-Omni 30B-A3B Instruct?

62 ptsGood (B) · 62 of 100 points: Model quality 22.1/45, Memory fit 10.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, with part of the model in system RAM

Runs with offload. At Q2_K it needs about 16.1 GB of 12.0 GB usable, with an estimated speed of 52.9 tok/s.

Best quant
Q2_K
Generation speed
52.9 tok/s
Prompt processing
6,166 tok/s
First token (1K prompt)
0.3 s
Largest safe context
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Download Qwen3-Omni 30B-A3B Instruct

Quantized files · GGUF

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

huggingface.co/ggml-org/Qwen3-Omni-30B-A3B-Instruct-GGUF (opens in a new tab)

ollama run hf.co/ggml-org/Qwen3-Omni-30B-A3B-Instruct-GGUF

Original weights · Hugging Face

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

huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Instruct (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.22.1 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.10.0 / 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.15.0 / 15
Total62.1 / 10062 ptsGood (B) · 62 of 100 points: Model quality 22.1/45, Memory fit 10.0/25, Speed 15.0/15, 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 NVIDIA GeForce RTX 4070 SUPER

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 16.1 GB 12.0 GB 52.9 tok/s Runs with offload 62 ptsGood (B) · 62 of 100 points: Model quality 22.1/45, Memory fit 10.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q3_K_M 19.3 GB 12.0 GB 32.2 tok/s Heavy offload 58 ptsGood (B) · 58 of 100 points: Model quality 26.5/45, Memory fit 4.0/25, Speed 13.5/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q4_K_M 23.5 GB 12.0 GB 20.8 tok/s Heavy offload 59 ptsGood (B) · 59 of 100 points: Model quality 29.9/45, Memory fit 4.0/25, Speed 10.8/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 27.0 GB 12.0 GB 15.7 tok/s Heavy offload 58 ptsGood (B) · 58 of 100 points: Model quality 30.6/45, Memory fit 4.0/25, Speed 9.4/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q6_K 30.9 GB 12.0 GB 12.3 tok/s Heavy offload 58 ptsGood (B) · 58 of 100 points: Model quality 31.2/45, Memory fit 4.0/25, Speed 8.3/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q8_0 39.4 GB 12.0 GB — Won't run 9 ptsWon't run (F) · 9 of 100 points: Model quality 9.5/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF (opens in a new tab)
F16 72.5 GB 12.0 GB — Won't run 9 ptsWon't run (F) · 9 of 100 points: Model quality 9.5/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 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.