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Can the AMD Ryzen AI Max+ 395 (128 GB) run DeepSeek Coder V2 (236B)?

51Fair quality (C) · 51 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 58/100 (quality, fit, speed and memory use) sets the ranking.

Yes, it runs well (over GPU memory limit)

Runs well (over GPU memory limit). At Q2_K it needs about 103 GB of 96.0 GB usable, with an estimated speed of 16.9 tok/s.

Best quant
Q2_K
Generation speed
16.9 tok/s
Prompt processing
1,754 tok/s
First token (1K prompt)
0.6 s
Largest safe context
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Best app to run it on the AMD Ryzen AI Max+ 395 (128 GB)

On Windows

Lemonade

Desktop app · runs on llama.cpp, ONNX Runtime GenAI (Ryzen AI NPU)

  • Splits the model between GPU memory and system RAM, which this setup needs.
  • Built for Ryzen AI and Strix Halo, including NPU + iGPU modes on Windows.
lemonade pull lmstudio-community/DeepSeek-Coder-V2-Instruct-0724-GGUF:Q2_K
  • llama.cpp Splits the model between GPU memory and system RAM, which this setup needs.
  • LM Studio Splits the model between GPU memory and system RAM, which this setup needs.

On Linux

Lemonade

Desktop app · runs on llama.cpp, ONNX Runtime GenAI (Ryzen AI NPU)

  • Splits the model between GPU memory and system RAM, which this setup needs.
  • Built for Ryzen AI and Strix Halo, including NPU + iGPU modes on Windows.
lemonade pull lmstudio-community/DeepSeek-Coder-V2-Instruct-0724-GGUF:Q2_K
  • llama.cpp Splits the model between GPU memory and system RAM, which this setup needs.
  • LM Studio Splits the model between GPU memory and system RAM, which this setup needs.

Want an agent? DeepSeek Coder V2 (236B) supports tool use, so you can pair a llama.cpp or MLX LM server with one of these. Apps that run on this computer come first.

Coding agents

Personal assistants

How we choose: the files published for this model, your operating system and GPU, whether it fits fully in memory, and published speed tests (MLX vs llama.cpp on Apple silicon, vLLM vs llama.cpp vs Ollama on NVIDIA). Details.

Download DeepSeek Coder V2 (236B)

Recommended for the AMD Ryzen AI Max+ 395 (128 GB): 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.

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

ollama run deepseek-coder-v2:236b-instruct-q2_K

Quantized files · GGUF

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

huggingface.co/lmstudio-community/DeepSeek-Coder-V2-Instruct-0724-GGUF (opens in a new tab)

ollama run hf.co/lmstudio-community/DeepSeek-Coder-V2-Instruct-0724-GGUF

Original weights · Hugging Face

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

huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Instruct-0724 (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 2 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 51Fair quality (C) · 51 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 58/100 (quality, fit, speed and memory use) sets the ranking.
How capable the model itself is at Q2_K, from its editorial quality tier scaled by the quantization or precision. It’s the same on any hardware that runs this variant. Scale: A+ 85+ · A 70+ · B 55+ · C 40+ · D under 40.
Runs Runs wellover GPU memory limit
How well it runs on the AMD Ryzen AI Max+ 395 (128 GB): speed, capped by how well it fits in memory. Runs great: 30+ tokens/s (or near the image, video or decision speed target) · Runs well: 10+ tokens/s · Slow: 3+ tokens/s · Very slow: under 3 · Won’t run: doesn’t fit even with offload. A tight fit or RAM offload caps it at Runs well; heavy offload caps it at Slow.

Match score

To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.23.3 / 45
Memory fitFull marks when the model fits in the share of unified memory the GPU can use; fewer when it goes past that limit.10.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.9.7 / 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
Match score58.1 / 100

The match score orders results; it is not shown as a grade. Quality and Runs are the two ratings in the tables.

Every quantization on the AMD Ryzen AI Max+ 395 (128 GB)

Quant Memory needed Available Speed Runs Quality Download
Q2_K 103 GB 96.0 GB 16.9 tok/s Runs wellover GPU memory limit 51Fair quality (C) · 51 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 58/100 (quality, fit, speed and memory use) sets the ranking.
Q3_K_M 124 GB 96.0 GB — Won't run 62Good quality (B) · 62 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 8/100 (quality, fit, speed and memory use) sets the ranking. GGUF (Q3_K_L) · part 1 of 4 (opens in a new tab)
Q4_K_M 153 GB 96.0 GB — Won't run 70Great quality (A) · 70 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking. GGUF · part 1 of 4 (opens in a new tab)
Q5_K_M 176 GB 96.0 GB — Won't run 71Great quality (A) · 71 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking.
Q6_K 202 GB 96.0 GB — Won't run 73Great quality (A) · 73 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking. GGUF · part 1 of 5 (opens in a new tab)
Q8_0 259 GB 96.0 GB — Won't run 74Great quality (A) · 74 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking. GGUF · part 1 of 7 (opens in a new tab)
F16 480 GB 96.0 GB — Won't run 74Great quality (A) · 74 of 100: how capable the model is at F16, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking. 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

Quick answers

How much memory does DeepSeek Coder V2 (236B) need on the AMD Ryzen AI Max+ 395 128GB?

At Q2_K it needs about 103 GB. The AMD Ryzen AI Max+ 395 128GB has 96.0 GB usable.

How fast is DeepSeek Coder V2 (236B) on the AMD Ryzen AI Max+ 395 128GB?

About 16.9 tok/s at Q2_K, an estimate from the hardware’s memory bandwidth and the size of the model.

Which quantization of DeepSeek Coder V2 (236B) should I use on the AMD Ryzen AI Max+ 395 128GB?

Q2_K. Of the versions that fit, it is the one that runs best; when two run equally well, the check prefers the higher-rated one.

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.

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