Qwen2.5 Coder 0.5B Instruct on AMD Ryzen AI 9 HX 470 (DDR5 SO-DIMM) (32 GB)
Can the AMD Ryzen AI 9 HX 470 (DDR5 SO-DIMM) (32 GB) run Qwen2.5 Coder 0.5B Instruct?
Yes, it runs well
Runs well. At F16 it needs about 3.6 GB of 24.0 GB usable, with an estimated speed of 45.3 tok/s.
- Best quant
F16- Generation speed
- 45.3 tok/s
- Prompt processing
- 32,139 tok/s
- First token (1K prompt)
- 0.3 s
- Largest safe context
- 32K
Download Qwen2.5 Coder 0.5B Instruct
Recommended for the AMD Ryzen AI 9 HX 470 (DDR5 SO-DIMM) (32 GB): 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 qwen2.5-coder:0.5b-instruct-fp16Quantized 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/Qwen/Qwen2.5-Coder-0.5B-Instruct-GGUF (opens in a new tab)
ollama run hf.co/Qwen/Qwen2.5-Coder-0.5B-Instruct-GGUF:FP16Original weights · Hugging Face
Full-precision files from Alibaba, for fine-tuning, vLLM, Transformers.
huggingface.co/Qwen/Qwen2.5-Coder-0.5B-Instruct (opens in a new tab)
How the C grade is scored
Every result gets up to 100 points from four parts. The points decide the letter grade.
| Model quality | 3.6 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 15.0 / 15 | |
| Memory use | 3.5 / 15 | |
| Total | 47.1 / 100 | 47 ptsUsable (C) · 47 of 100 points: Model quality 3.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 3.5/15 |
Every quantization on the AMD Ryzen AI 9 HX 470 (DDR5 SO-DIMM) (32 GB)
| Quant | Memory needed | Available | Speed | Fit | Grade · points | Download |
|---|---|---|---|---|---|---|
Q2_K | 2.8 GB | 24.0 GB | 317 tok/s | Runs well | 45 ptsUsable (C) · 45 of 100 points: Model quality 2.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 2.7/15 | GGUF (opens in a new tab) |
Q3_K_M | 2.9 GB | 24.0 GB | 250 tok/s | Runs well | 45 ptsUsable (C) · 45 of 100 points: Model quality 3.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 2.8/15 | GGUF (opens in a new tab) |
Q4_K_M | 2.9 GB | 24.0 GB | 193 tok/s | Runs well | 46 ptsUsable (C) · 46 of 100 points: Model quality 3.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 2.8/15 | GGUF (opens in a new tab) |
Q5_K_M | 3.0 GB | 24.0 GB | 160 tok/s | Runs well | 46 ptsUsable (C) · 46 of 100 points: Model quality 3.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 2.9/15 | GGUF (opens in a new tab) |
Q6_K | 3.0 GB | 24.0 GB | 134 tok/s | Runs well | 46 ptsUsable (C) · 46 of 100 points: Model quality 3.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 2.9/15 | GGUF (opens in a new tab) |
Q8_0 | 3.1 GB | 24.0 GB | 98.4 tok/s | Runs well | 46 ptsUsable (C) · 46 of 100 points: Model quality 3.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 3.0/15 | GGUF (opens in a new tab) |
F16 | 3.6 GB | 24.0 GB | 45.3 tok/s | Runs well | 47 ptsUsable (C) · 47 of 100 points: Model quality 3.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 3.5/15 | 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
- 49 ptsUsable (C) · 49 of 100 points: Model quality 3.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.0/15 NVIDIA GeForce RTX 4060
- 49 ptsUsable (C) · 49 of 100 points: Model quality 3.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.5/15 Apple M4 (16 GB)
- 48 ptsUsable (C) · 48 of 100 points: Model quality 3.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.5/15 Apple M1 (16 GB)
- 47 ptsUsable (C) · 47 of 100 points: Model quality 3.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.4/15 Intel Arc B580
- 47 ptsUsable (C) · 47 of 100 points: Model quality 3.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.4/15 NVIDIA GeForce RTX 3060 12GB
- 47 ptsUsable (C) · 47 of 100 points: Model quality 3.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.4/15 NVIDIA GeForce RTX 4070 SUPER
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.