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Can the NVIDIA GeForce RTX 3060 Ti run TMax 9B?

86 ptsExcellent (S) · 86 of 100 points: Model quality 31.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q4_K_M it needs about 6.7 GB of 8.0 GB usable, with an estimated speed of 61.4 tok/s.

Best quant
Q4_K_M
Generation speed
61.4 tok/s
Prompt processing
1,303 tok/s
First token (1K prompt)
0.8 s
Largest safe context
45K

Download TMax 9B

Original weights · Hugging Face

Full-precision files from Ai2, for fine-tuning, vLLM, Transformers.

huggingface.co/allenai/tmax-9b (opens in a new tab)

No sign-in needed.

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.31.6 / 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
Total86.6 / 10086 ptsExcellent (S) · 86 of 100 points: Model quality 31.6/45, 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 Ti

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 4.8 GB 8.0 GB 101 tok/s Runs well 77 ptsGreat (A) · 77 of 100 points: Model quality 23.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.0/15 All files (opens in a new tab)
Q3_K_M 5.7 GB 8.0 GB 79.4 tok/s Runs well 82 ptsGreat (A) · 82 of 100 points: Model quality 28.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q4_K_M 6.7 GB 8.0 GB 61.4 tok/s Runs well 86 ptsExcellent (S) · 86 of 100 points: Model quality 31.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q5_K_M 7.6 GB 8.0 GB 50.8 tok/s Tight fit 86 ptsExcellent (S) · 86 of 100 points: Model quality 32.3/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q6_K 8.6 GB 8.0 GB 28.9 tok/s Runs with offload 70 ptsGood (B) · 70 of 100 points: Model quality 33.0/45, Memory fit 10.0/25, Speed 12.8/15, Memory use 15.0/15 All files (opens in a new tab)
Q8_0 10.8 GB 8.0 GB 11.8 tok/s Runs with offload 66 ptsGood (B) · 66 of 100 points: Model quality 33.3/45, Memory fit 10.0/25, Speed 8.1/15, Memory use 15.0/15 All files (opens in a new tab)
F16 19.2 GB 8.0 GB 3.2 tok/s Heavy offload 56 ptsUsable (C) · 56 of 100 points: Model quality 33.3/45, Memory fit 4.0/25, Speed 4.2/15, 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.