Baichuan M3 235B-A22B on NVIDIA GeForce RTX 5060 Ti 8GB

Can the NVIDIA GeForce RTX 5060 Ti 8GB run Baichuan M3 235B-A22B?

7 pts

No, it doesn’t fit

No. Baichuan M3 235B-A22B needs about 96.6 GB even at Q2_K; the NVIDIA GeForce RTX 5060 Ti 8GB has 8.0 GB usable.

Download Baichuan M3 235B-A22B

Recommended: Q2_K. Every other quantization has its own download link in the table below.

Quantized files · GGUF

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

Download the Q2_K file (opens in a new tab)

huggingface.co/mradermacher/Baichuan-M3-235B-i1-GGUF (opens in a new tab)

ollama run hf.co/mradermacher/Baichuan-M3-235B-i1-GGUF:Q2_K

Original weights · Hugging Face

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

huggingface.co/baichuan-inc/Baichuan-M3-235B (opens in a new tab)

No sign-in needed.

Links checked 6 days ago against Hugging Face, Ollama and GitHub.

How the F 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.	7.9 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	0.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	0.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	0.0 / 15
Total	7.9 / 100	7 ptsWon't run (F) · 7 of 100 points: Model quality 7.9/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15

It doesn’t fit, so only a reduced share of the quality points counts and fit, speed and memory use score zero.

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the NVIDIA GeForce RTX 5060 Ti 8GB

Quant	Memory needed	Available	Speed	Fit	Grade · points	Download
`Q2_K`	96.6 GB	8.0 GB	—	Won't run	7 ptsWon't run (F) · 7 of 100 points: Model quality 7.9/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`Q3_K_M`	118 GB	8.0 GB	—	Won't run	9 ptsWon't run (F) · 9 of 100 points: Model quality 9.5/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`Q4_K_M`	146 GB	8.0 GB	—	Won't run	10 ptsWon't run (F) · 10 of 100 points: Model quality 10.8/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`Q5_K_M`	169 GB	8.0 GB	—	Won't run	10 ptsWon't run (F) · 10 of 100 points: Model quality 11.0/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`Q6_K`	195 GB	8.0 GB	—	Won't run	11 ptsWon't run (F) · 11 of 100 points: Model quality 11.2/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`Q8_0`	252 GB	8.0 GB	—	Won't run	11 ptsWon't run (F) · 11 of 100 points: Model quality 11.3/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF files (opens in a new tab)
`F16`	473 GB	8.0 GB	—	Won't run	11 ptsWon't run (F) · 11 of 100 points: Model quality 11.3/45, 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.

Hardware that can run it

86 ptsExcellent (S) · 86 of 100 points: Model quality 35.9/45, Memory fit 25.0/25, Speed 10.5/15, Memory use 15.0/15 Apple M3 Ultra (256 GB) Q4_K_M · 19.7 tok/s
82 ptsGreat (A) · 82 of 100 points: Model quality 31.8/45, Memory fit 24.0/25, Speed 11.8/15, Memory use 15.0/15 Apple M2 Ultra (192 GB) Q3_K_M · 24.8 tok/s
82 ptsGreat (A) · 82 of 100 points: Model quality 35.9/45, Memory fit 25.0/25, Speed 10.5/15, Memory use 10.6/15 Apple M3 Ultra (512 GB) Q4_K_M · 19.7 tok/s
73 ptsGreat (A) · 73 of 100 points: Model quality 26.5/45, Memory fit 24.0/25, Speed 8.4/15, Memory use 15.0/15 NVIDIA GB10 (128 GB) Q2_K · 12.5 tok/s
65 ptsGood (B) · 65 of 100 points: Model quality 26.5/45, Memory fit 10.0/25, Speed 13.9/15, Memory use 15.0/15 NVIDIA RTX PRO 6000 Blackwell Q2_K · 34.5 tok/s
61 ptsGood (B) · 61 of 100 points: Model quality 26.5/45, Memory fit 10.0/25, Speed 10.1/15, Memory use 15.0/15 Apple M4 Max (128 GB) Q2_K · 18.3 tok/s

Models that do run on the NVIDIA GeForce RTX 5060 Ti 8GB

86 ptsExcellent (S) · 86 of 100 points: Model quality 32.9/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 Ornith 1.5 9B Q4_K_M · 57.0 tok/s
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 TMax 9B Q4_K_M · 61.4 tok/s
86 ptsExcellent (S) · 86 of 100 points: Model quality 32.5/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 Qwen3.5 9B Q4_K_M · 57.0 tok/s
86 ptsExcellent (S) · 86 of 100 points: Model quality 32.1/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 Ornith 1.0 9B Q4_K_M · 57.0 tok/s
85 ptsExcellent (S) · 85 of 100 points: Model quality 31.4/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 Gemma 4 12B Q3_K_M · 59.4 tok/s

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.