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Can the NVIDIA GeForce RTX 5090 run Yi 1.5 34B Chat?

76 ptsGreat (A) · 76 of 100 points: Model quality 21.4/45, 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 24.2 GB of 32.0 GB usable, with an estimated speed of 64.0 tok/s.

Best quant
Q4_K_M
Generation speed
64.0 tok/s
Prompt processing
2,194 tok/s
First token (1K prompt)
0.5 s
Largest safe context
4K

Download Yi 1.5 34B Chat

Recommended for the NVIDIA GeForce RTX 5090: Q4_K_M. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run yi:34b-chat-v1.5-q4_K_M

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

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

Download the Q4_K_M file (opens in a new tab)

huggingface.co/lmstudio-community/Yi-1.5-34B-Chat-GGUF (opens in a new tab)

ollama run hf.co/lmstudio-community/Yi-1.5-34B-Chat-GGUF:Q4_K_M

Original weights · Hugging Face

Full-precision files from 01.AI, for fine-tuning, vLLM, Transformers.

huggingface.co/01-ai/Yi-1.5-34B-Chat (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from 01.AI. The weights themselves download from Hugging Face.

github.com/01-ai/Yi-1.5 (opens in a new tab)

git clone https://github.com/01-ai/Yi-1.5

Links checked 1 week 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.21.4 / 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
Total76.4 / 10076 ptsGreat (A) · 76 of 100 points: Model quality 21.4/45, 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 5090

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 17.0 GB 32.0 GB 105 tok/s Runs well 67 ptsGood (B) · 67 of 100 points: Model quality 15.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.2/15 GGUF (opens in a new tab)
Q3_K_M 20.1 GB 32.0 GB 82.7 tok/s Runs well 73 ptsGreat (A) · 73 of 100 points: Model quality 18.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.5/15 GGUF (Q3_K_L) (opens in a new tab)
Q4_K_M 24.2 GB 32.0 GB 64.0 tok/s Runs well 76 ptsGreat (A) · 76 of 100 points: Model quality 21.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 27.6 GB 32.0 GB 52.8 tok/s Tight fit 75 ptsGreat (A) · 75 of 100 points: Model quality 21.8/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q6_K 31.4 GB 32.0 GB 44.4 tok/s Tight fit 76 ptsGreat (A) · 76 of 100 points: Model quality 22.3/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 39.7 GB 32.0 GB 5.1 tok/s Runs with offload 52 ptsUsable (C) · 52 of 100 points: Model quality 22.5/45, Memory fit 10.0/25, Speed 5.3/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 72.0 GB 32.0 GB — Won't run 6 ptsWon't run (F) · 6 of 100 points: Model quality 6.8/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 Original weights (opens in a new tab)

Memory figures assume 4K 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.