Yi 1.5 34B Chat on AMD Radeon RX 7900 XTX

Can the AMD Radeon RX 7900 XTX run Yi 1.5 34B Chat?

73 pts

Yes, it runs well

Runs well. At Q3_K_M it needs about 19.7 GB of 24.0 GB usable, with an estimated speed of 38.1 tok/s.

Best quant: Q3_K_M
Generation speed: 38.1 tok/s
Prompt processing: 2,214 tok/s
First token (1K prompt): 0.5 s
Largest safe context: 4K

Download Yi 1.5 34B Chat

Recommended for the AMD Radeon RX 7900 XTX: Q3_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-q3_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 Q3_K_M (Q3_K_L) 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:Q3_K_L

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 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.	18.9 / 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.	14.6 / 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
Total	73.5 / 100	73 ptsGreat (A) · 73 of 100 points: Model quality 18.9/45, Memory fit 25.0/25, Speed 14.6/15, 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 AMD Radeon RX 7900 XTX

Quant	Memory needed	Available	Speed	Fit	Grade · points	Download
`Q2_K`	16.6 GB	24.0 GB	48.5 tok/s	Runs well	70 ptsGood (B) · 70 of 100 points: Model quality 15.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q3_K_M`	19.7 GB	24.0 GB	38.1 tok/s	Runs well	73 ptsGreat (A) · 73 of 100 points: Model quality 18.9/45, Memory fit 25.0/25, Speed 14.6/15, Memory use 15.0/15	GGUF (Q3_K_L) (opens in a new tab)
`Q4_K_M`	23.8 GB	24.0 GB	29.5 tok/s	Tight fit	73 ptsGreat (A) · 73 of 100 points: Model quality 21.4/45, Memory fit 24.0/25, Speed 12.9/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q5_K_M`	27.2 GB	24.0 GB	9.7 tok/s	Runs with offload	54 ptsUsable (C) · 54 of 100 points: Model quality 21.8/45, Memory fit 10.0/25, Speed 7.4/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q6_K`	31.0 GB	24.0 GB	5.3 tok/s	Runs with offload	52 ptsUsable (C) · 52 of 100 points: Model quality 22.3/45, Memory fit 10.0/25, Speed 5.5/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q8_0`	39.3 GB	24.0 GB	2.6 tok/s	Heavy offload	45 ptsUsable (C) · 45 of 100 points: Model quality 22.5/45, Memory fit 4.0/25, Speed 3.8/15, Memory use 15.0/15	GGUF (opens in a new tab)
`F16`	71.6 GB	24.0 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

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 NVIDIA GeForce RTX 5090 Q4_K_M · 64.0 tok/s
74 ptsGreat (A) · 74 of 100 points: Model quality 21.4/45, Memory fit 24.0/25, Speed 14.2/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090 Q4_K_M · 36.0 tok/s
74 ptsGreat (A) · 74 of 100 points: Model quality 21.4/45, Memory fit 24.0/25, Speed 13.7/15, Memory use 15.0/15 NVIDIA GeForce RTX 3090 Q4_K_M · 33.4 tok/s
70 ptsGood (B) · 70 of 100 points: Model quality 22.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.3/15 NVIDIA RTX PRO 6000 Blackwell Q6_K · 44.4 tok/s
68 ptsGood (B) · 68 of 100 points: Model quality 21.4/45, Memory fit 25.0/25, Speed 9.7/15, Memory use 12.7/15 Apple M4 Max (64 GB) Q4_K_M · 16.8 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.