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Can the NVIDIA GeForce RTX 4060 run Yi Coder 1.5B Chat?

62 ptsGood (B) · 62 of 100 points: Model quality 7.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At F16 it needs about 5.6 GB of 8.0 GB usable, with an estimated speed of 52.9 tok/s.

Best quant
F16
Generation speed
52.9 tok/s
Prompt processing
7,346 tok/s
First token (1K prompt)
0.3 s
Largest safe context
20K

Download Yi Coder 1.5B Chat

Recommended for the NVIDIA GeForce RTX 4060: F16. 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-coder:1.5b-chat-fp16

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 F16 file (opens in a new tab)

huggingface.co/bartowski/Yi-Coder-1.5B-Chat-GGUF (opens in a new tab)

ollama run hf.co/bartowski/Yi-Coder-1.5B-Chat-GGUF:F16

Original weights · Hugging Face

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

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

No sign-in needed.

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

How the B 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.7.2 / 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
Total62.2 / 10062 ptsGood (B) · 62 of 100 points: Model quality 7.2/45, 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 4060

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 3.2 GB 8.0 GB 371 tok/s Runs well 54 ptsUsable (C) · 54 of 100 points: Model quality 5.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.2/15 GGUF (opens in a new tab)
Q3_K_M 3.3 GB 8.0 GB 292 tok/s Runs well 55 ptsUsable (C) · 55 of 100 points: Model quality 6.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.6/15 GGUF (opens in a new tab)
Q4_K_M 3.5 GB 8.0 GB 226 tok/s Runs well 56 ptsUsable (C) · 56 of 100 points: Model quality 6.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.1/15 GGUF (opens in a new tab)
Q5_K_M 3.7 GB 8.0 GB 186 tok/s Runs well 57 ptsUsable (C) · 57 of 100 points: Model quality 7.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.6/15 GGUF (opens in a new tab)
Q6_K 3.8 GB 8.0 GB 157 tok/s Runs well 58 ptsGood (B) · 58 of 100 points: Model quality 7.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.0/15 GGUF (opens in a new tab)
Q8_0 4.2 GB 8.0 GB 115 tok/s Runs well 59 ptsGood (B) · 59 of 100 points: Model quality 7.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.1/15 GGUF (opens in a new tab)
F16 5.6 GB 8.0 GB 52.9 tok/s Runs well 62 ptsGood (B) · 62 of 100 points: Model quality 7.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab) 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.