Qwen3 Coder Next (80B-A3B) on AMD Ryzen AI Max+ 395 (128 GB)
Can the AMD Ryzen AI Max+ 395 (128 GB) run Qwen3 Coder Next (80B-A3B)?
Yes, it runs well
Runs well. At Q5_K_M it needs about 65.0 GB of 96.0 GB usable, with an estimated speed of 37.3 tok/s.
- Best quant
Q5_K_M- Generation speed
- 37.3 tok/s
- Prompt processing
- 12,276 tok/s
- First token (1K prompt)
- 0.3 s
- Largest safe context
- 256K
Download Qwen3 Coder Next (80B-A3B)
Recommended for the AMD Ryzen AI Max+ 395 (128 GB): Q5_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 qwen3-coder-nextQuantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q5_K_M files (opens in a new tab)
huggingface.co/Qwen/Qwen3-Coder-Next-GGUF (opens in a new tab)
ollama run hf.co/Qwen/Qwen3-Coder-Next-GGUFOriginal weights · Hugging Face
Full-precision files from Alibaba, for fine-tuning, vLLM, Transformers.
Official repo · GitHub
Reference code, inference scripts and docs from Alibaba. The weights themselves download from Hugging Face.
github.com/QwenLM/Qwen3-Coder (opens in a new tab)
git clone https://github.com/QwenLM/Qwen3-CoderHow the S grade is scored
Every result gets up to 100 points from four parts. The points decide the letter grade.
| Model quality | 37.5 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 14.5 / 15 | |
| Memory use | 15.0 / 15 | |
| Total | 92.0 / 100 | 92 ptsExcellent (S) · 92 of 100 points: Model quality 37.5/45, Memory fit 25.0/25, Speed 14.5/15, Memory use 15.0/15 |
Every quantization on the AMD Ryzen AI Max+ 395 (128 GB)
| Quant | Memory needed | Available | Speed | Fit | Grade · points | Download |
|---|---|---|---|---|---|---|
Q2_K | 40.3 GB | 96.0 GB | 74.1 tok/s | Runs well | 76 ptsGreat (A) · 76 of 100 points: Model quality 27.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.7/15 | GGUF files (opens in a new tab) |
Q3_K_M | 47.5 GB | 96.0 GB | 58.3 tok/s | Runs well | 83 ptsGreat (A) · 83 of 100 points: Model quality 32.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.4/15 | GGUF files (opens in a new tab) |
Q4_K_M | 57.1 GB | 96.0 GB | 45.1 tok/s | Runs well | 90 ptsExcellent (S) · 90 of 100 points: Model quality 36.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.7/15 | GGUF · folder (opens in a new tab) |
Q5_K_M | 65.0 GB | 96.0 GB | 37.3 tok/s | Runs well | 92 ptsExcellent (S) · 92 of 100 points: Model quality 37.5/45, Memory fit 25.0/25, Speed 14.5/15, Memory use 15.0/15 | GGUF · folder (opens in a new tab) |
Q6_K | 73.8 GB | 96.0 GB | 31.3 tok/s | Runs well | 91 ptsExcellent (S) · 91 of 100 points: Model quality 38.3/45, Memory fit 25.0/25, Speed 13.3/15, Memory use 15.0/15 | GGUF · folder (opens in a new tab) |
Q8_0 | 92.9 GB | 96.0 GB | 23.0 tok/s | Tight fit | 89 ptsExcellent (S) · 89 of 100 points: Model quality 38.7/45, Memory fit 24.0/25, Speed 11.4/15, Memory use 15.0/15 | GGUF · folder (opens in a new tab) |
F16 | 168 GB | 96.0 GB | — | Won't run | 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.6/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 | GGUF · folder (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
- 93 ptsExcellent (S) · 93 of 100 points: Model quality 38.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 Apple M2 Ultra (192 GB)
- 93 ptsExcellent (S) · 93 of 100 points: Model quality 38.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 Apple M4 Max (128 GB)
- 93 ptsExcellent (S) · 93 of 100 points: Model quality 38.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA RTX PRO 6000 Blackwell
- 93 ptsExcellent (S) · 93 of 100 points: Model quality 38.3/45, Memory fit 25.0/25, Speed 14.8/15, Memory use 15.0/15 NVIDIA GB10 (128 GB)
- 90 ptsExcellent (S) · 90 of 100 points: Model quality 38.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.1/15 Apple M3 Ultra (256 GB)
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.