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Can the NVIDIA GeForce RTX 3060 12GB run Qwen2 7B Instruct?

74 ptsGreat (A) · 74 of 100 points: Model quality 19.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q6_K it needs about 7.9 GB of 12.0 GB usable, with an estimated speed of 40.2 tok/s.

Best quant
Q6_K
Generation speed
40.2 tok/s
Prompt processing
1,200 tok/s
First token (1K prompt)
0.9 s
Largest safe context
32K

Download Qwen2 7B Instruct

Recommended for the NVIDIA GeForce RTX 3060 12GB: Q6_K. 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 qwen2:7b-instruct-q6_K

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 Q6_K file (opens in a new tab)

huggingface.co/Qwen/Qwen2-7B-Instruct-GGUF (opens in a new tab)

ollama run hf.co/Qwen/Qwen2-7B-Instruct-GGUF:Q6_K

Original weights · Hugging Face

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

huggingface.co/Qwen/Qwen2-7B-Instruct (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.19.6 / 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.15.0 / 15
Total74.6 / 10074 ptsGreat (A) · 74 of 100 points: Model quality 19.6/45, Memory fit 25.0/25, 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 3060 12GB

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 4.7 GB 12.0 GB 95.2 tok/s Runs well 62 ptsGood (B) · 62 of 100 points: Model quality 13.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.1/15 GGUF (opens in a new tab)
Q3_K_M 5.4 GB 12.0 GB 75.0 tok/s Runs well 67 ptsGood (B) · 67 of 100 points: Model quality 16.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.4/15 GGUF (opens in a new tab)
Q4_K_M 6.3 GB 12.0 GB 58.0 tok/s Runs well 70 ptsGood (B) · 70 of 100 points: Model quality 18.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.1/15 GGUF (opens in a new tab)
Q5_K_M 7.1 GB 12.0 GB 47.9 tok/s Runs well 72 ptsGreat (A) · 72 of 100 points: Model quality 19.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.6/15 GGUF (opens in a new tab)
Q6_K 7.9 GB 12.0 GB 40.2 tok/s Runs well 74 ptsGreat (A) · 74 of 100 points: Model quality 19.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 9.7 GB 12.0 GB 29.5 tok/s Runs well 72 ptsGreat (A) · 72 of 100 points: Model quality 19.8/45, Memory fit 25.0/25, Speed 12.9/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 16.9 GB 12.0 GB 5.6 tok/s Heavy offload 44 ptsUsable (C) · 44 of 100 points: Model quality 19.8/45, Memory fit 4.0/25, Speed 5.6/15, 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.