Qwen3Guard Gen 4B on Intel Arc A580
Can the Intel Arc A580 run Qwen3Guard Gen 4B?
Yes, it runs well
Runs well. At Q6_K it needs about 4.9 GB of 8.0 GB usable and makes one decision in about 250 ms.
- Best quant
Q6_K- Time per decision
- 250 ms
- Decisions per second
- 4.0/s
- Input assumed
- 512 tokens
- Returns
- Fixed labels
Best app to run it on the Intel Arc A580
On Windows
- Supports Intel Arc through SYCL and Vulkan.
- Usually the first to support new model architectures.
llama-server -hf mradermacher/Qwen3Guard-Gen-4B-GGUF:Q6_KDownload Qwen3Guard Gen 4B
Recommended for the Intel Arc A580: Q6_K. Every other quantization has its own download link in the table below.
Quantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q6_K file (opens in a new tab)
huggingface.co/mradermacher/Qwen3Guard-Gen-4B-GGUF (opens in a new tab)
ollama run hf.co/mradermacher/Qwen3Guard-Gen-4B-GGUF:Q6_KOriginal weights · Hugging Face
Full-precision files from Alibaba, for fine-tuning, vLLM, Transformers.
How it’s rated
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.
| Precision | 37.4 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 9.5 / 15 | |
| Clarity | 12.0 / 15 | |
| Match score | 83.9 / 100 |
Every quantization on the Intel Arc A580
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q4_K_M | 4.0 GB | 8.0 GB | 226 ms | Runs well | 79Great quality (A) · 79 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 4.4 GB | 8.0 GB | 238 ms | Runs well | 81Great quality (A) · 81 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 4.9 GB | 8.0 GB | 250 ms | Runs well | 83Great quality (A) · 83 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 6.0 GB | 8.0 GB | 279 ms | Runs well | 84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 10.1 GB | 8.0 GB | 715 ms | Slowoffloads to RAM | 84Great quality (A) · 84 of 100: how capable the model is at F16, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) Original weights (opens in a new tab) |
Times are for one request with a 512-token input and about 6 tokens written. Batching servers process many requests at once.
Other hardware that runs it
-
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 7900 XTX
-
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4090
-
84Great quality (A) · 84 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5090
-
84Great quality (A) · 84 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA RTX PRO 6000 Blackwell
-
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5080
-
83Great quality (A) · 83 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 9070 XT
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.