Check my GPU

on

Can the NVIDIA GeForce RTX 3050 Ti Laptop GPU run TMax 4B?

80 ptsGreat (A) · 80 of 100 points: Model quality 26.1/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q4_K_M it needs about 3.6 GB of 4.0 GB usable, with an estimated speed of 56.0 tok/s.

Best quant
Q4_K_M
Generation speed
56.0 tok/s
Prompt processing
906 tok/s
First token (1K prompt)
1.1 s
Largest safe context
18K

Download TMax 4B

Original weights · Hugging Face

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

huggingface.co/allenai/tmax-4b (opens in a new tab)

No sign-in needed.

Links checked 6 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.26.1 / 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
Total80.1 / 10080 ptsGreat (A) · 80 of 100 points: Model quality 26.1/45, 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 3050 Ti Laptop GPU

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 2.8 GB 4.0 GB 91.9 tok/s Runs well 74 ptsGreat (A) · 74 of 100 points: Model quality 19.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q3_K_M 3.1 GB 4.0 GB 72.4 tok/s Runs well 78 ptsGreat (A) · 78 of 100 points: Model quality 23.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q4_K_M 3.6 GB 4.0 GB 56.0 tok/s Tight fit 80 ptsGreat (A) · 80 of 100 points: Model quality 26.1/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q5_K_M 4.1 GB 4.0 GB 44.6 tok/s Runs with offload 66 ptsGood (B) · 66 of 100 points: Model quality 26.6/45, Memory fit 10.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q6_K 4.5 GB 4.0 GB 30.3 tok/s Runs with offload 65 ptsGood (B) · 65 of 100 points: Model quality 27.2/45, Memory fit 10.0/25, Speed 13.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q8_0 5.5 GB 4.0 GB 17.3 tok/s Heavy offload 56 ptsUsable (C) · 56 of 100 points: Model quality 27.5/45, Memory fit 4.0/25, Speed 9.9/15, Memory use 15.0/15 All files (opens in a new tab)
F16 9.5 GB 4.0 GB 5.9 tok/s Heavy offload 52 ptsUsable (C) · 52 of 100 points: Model quality 27.5/45, Memory fit 4.0/25, Speed 5.8/15, 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.