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Can the NVIDIA GeForce RTX 5080 Laptop GPU run TMax 27B?

88 ptsExcellent (S) · 88 of 100 points: Model quality 34.0/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q3_K_M it needs about 15.3 GB of 16.0 GB usable, with an estimated speed of 52.0 tok/s.

Best quant
Q3_K_M
Generation speed
52.0 tok/s
Prompt processing
1,079 tok/s
First token (1K prompt)
0.9 s
Largest safe context
17K

Download TMax 27B

Original weights · Hugging Face

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

huggingface.co/allenai/tmax-27b (opens in a new tab)

No sign-in needed.

Links checked 6 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.34.0 / 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.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
Total88.0 / 10088 ptsExcellent (S) · 88 of 100 points: Model quality 34.0/45, Memory fit 24.0/25, 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 5080 Laptop GPU

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 12.9 GB 16.0 GB 66.0 tok/s Runs well 83 ptsGreat (A) · 83 of 100 points: Model quality 28.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q3_K_M 15.3 GB 16.0 GB 52.0 tok/s Tight fit 88 ptsExcellent (S) · 88 of 100 points: Model quality 34.0/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q4_K_M 18.6 GB 16.0 GB 13.6 tok/s Runs with offload 72 ptsGreat (A) · 72 of 100 points: Model quality 38.5/45, Memory fit 10.0/25, Speed 8.7/15, Memory use 15.0/15 All files (opens in a new tab)
Q5_K_M 21.4 GB 16.0 GB 7.5 tok/s Runs with offload 70 ptsGood (B) · 70 of 100 points: Model quality 39.3/45, Memory fit 10.0/25, Speed 6.5/15, Memory use 15.0/15 All files (opens in a new tab)
Q6_K 24.4 GB 16.0 GB 4.9 tok/s Heavy offload 64 ptsGood (B) · 64 of 100 points: Model quality 40.1/45, Memory fit 4.0/25, Speed 5.3/15, Memory use 15.0/15 All files (opens in a new tab)
Q8_0 30.9 GB 16.0 GB 2.8 tok/s Heavy offload 63 ptsGood (B) · 63 of 100 points: Model quality 40.5/45, Memory fit 4.0/25, Speed 3.9/15, Memory use 15.0/15 All files (opens in a new tab)
F16 56.7 GB 16.0 GB — Won't run 12 ptsWon't run (F) · 12 of 100 points: Model quality 12.2/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 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.