Check my GPU

on

Can the NVIDIA GB10 (128 GB) run Command R+ 104B (04-2024)?

72 ptsGreat (A) · 72 of 100 points: Model quality 28.5/45, Memory fit 25.0/25, Speed 3.5/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q6_K it needs about 97.1 GB of 115 GB usable, with an estimated speed of 2.2 tok/s.

Best quant
Q6_K
Generation speed
2.2 tok/s
Prompt processing
215 tok/s
First token (1K prompt)
4.8 s
Largest safe context
75K

Download Command R+ 104B (04-2024)

Quantized files · GGUF

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

huggingface.co/bartowski/c4ai-command-r-plus-GGUF (opens in a new tab)

ollama run hf.co/bartowski/c4ai-command-r-plus-GGUF

Original weights · Hugging Face

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

huggingface.co/CohereLabs/c4ai-command-r-plus (opens in a new tab)

Free Hugging Face account needed: accept the license on the model page and the download starts right away.

Links checked 7 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.28.5 / 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.3.5 / 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
Total72.1 / 10072 ptsGreat (A) · 72 of 100 points: Model quality 28.5/45, Memory fit 25.0/25, Speed 3.5/15, 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 GB10 (128 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 53.5 GB 115 GB 5.3 tok/s Runs well 61 ptsGood (B) · 61 of 100 points: Model quality 20.2/45, Memory fit 25.0/25, Speed 5.5/15, Memory use 10.7/15 GGUF (opens in a new tab)
Q3_K_M 62.8 GB 115 GB 4.2 tok/s Runs well 66 ptsGood (B) · 66 of 100 points: Model quality 24.2/45, Memory fit 25.0/25, Speed 4.8/15, Memory use 12.6/15 GGUF · folder (opens in a new tab)
Q4_K_M 75.3 GB 115 GB 3.2 tok/s Runs well 71 ptsGood (B) · 71 of 100 points: Model quality 27.4/45, Memory fit 25.0/25, Speed 4.3/15, Memory use 15.0/15 GGUF · folder (opens in a new tab)
Q5_K_M 85.7 GB 115 GB 2.7 tok/s Runs well 71 ptsGood (B) · 71 of 100 points: Model quality 27.9/45, Memory fit 25.0/25, Speed 3.9/15, Memory use 15.0/15 GGUF · folder (opens in a new tab)
Q6_K 97.1 GB 115 GB 2.2 tok/s Runs well 72 ptsGreat (A) · 72 of 100 points: Model quality 28.5/45, Memory fit 25.0/25, Speed 3.5/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q8_0 122 GB 115 GB — Won't run 8 ptsWon't run (F) · 8 of 100 points: Model quality 8.6/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF files (opens in a new tab)
F16 220 GB 115 GB — Won't run 8 ptsWon't run (F) · 8 of 100 points: Model quality 8.6/45, 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.