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Can the AMD Radeon RX 9060 XT 8GB run DeepSeek Coder V2 Lite (16B)?

70 ptsGood (B) · 70 of 100 points: Model quality 16.4/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q2_K it needs about 7.5 GB of 8.0 GB usable, with an estimated speed of 116 tok/s.

Best quant
Q2_K
Generation speed
116 tok/s
Prompt processing
13,227 tok/s
First token (1K prompt)
0.3 s
Largest safe context
22K

Download DeepSeek Coder V2 Lite (16B)

Recommended for the AMD Radeon RX 9060 XT 8GB: Q2_K. 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 deepseek-coder-v2:16b-lite-instruct-q2_K

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.

huggingface.co/lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF (opens in a new tab)

ollama run hf.co/lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF

Original weights · Hugging Face

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

huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct (opens in a new tab)

No sign-in needed.

Official repo · GitHub

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

github.com/deepseek-ai/DeepSeek-Coder-V2 (opens in a new tab)

git clone https://github.com/deepseek-ai/DeepSeek-Coder-V2

Links checked 1 week 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.16.4 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.24.0 / 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
Total70.4 / 10070 ptsGood (B) · 70 of 100 points: Model quality 16.4/45, Memory fit 24.0/25, 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 AMD Radeon RX 9060 XT 8GB

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 7.5 GB 8.0 GB 116 tok/s Tight fit 70 ptsGood (B) · 70 of 100 points: Model quality 16.4/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15
Q3_K_M 9.0 GB 8.0 GB 65.6 tok/s Runs with offload 59 ptsGood (B) · 59 of 100 points: Model quality 19.7/45, Memory fit 10.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (Q3_K_L) (opens in a new tab)
Q4_K_M 10.8 GB 8.0 GB 36.6 tok/s Runs with offload 61 ptsGood (B) · 61 of 100 points: Model quality 22.2/45, Memory fit 10.0/25, Speed 14.3/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 12.4 GB 8.0 GB 26.0 tok/s Heavy offload 53 ptsUsable (C) · 53 of 100 points: Model quality 22.7/45, Memory fit 4.0/25, Speed 12.1/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q6_K 14.1 GB 8.0 GB 19.6 tok/s Heavy offload 52 ptsUsable (C) · 52 of 100 points: Model quality 23.2/45, Memory fit 4.0/25, Speed 10.5/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 17.9 GB 8.0 GB 12.5 tok/s Heavy offload 50 ptsUsable (C) · 50 of 100 points: Model quality 23.4/45, Memory fit 4.0/25, Speed 8.4/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 32.7 GB 8.0 GB — Won't run 7 ptsWon't run (F) · 7 of 100 points: Model quality 7.0/45, 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.