Qwen3Guard Gen 4B on Intel Arc A380
Can the Intel Arc A380 run Qwen3Guard Gen 4B?
Yes, but slowly
Slow. At Q6_K it needs about 4.8 GB of 6.0 GB usable and makes one decision in about 723 ms.
- Best quant
Q6_K- Time per decision
- 723 ms
- Decisions per second
- 1.4/s
- Input assumed
- 512 tokens
- Returns
- Fixed labels
Best app to run it on the Intel Arc A380
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 A380: 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 | 5.6 / 15 | |
| Clarity | 12.0 / 15 | |
| Match score | 80.0 / 100 |
Every quantization on the Intel Arc A380
| Quant | Memory needed | Available | Time per decision | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q4_K_M | 3.9 GB | 6.0 GB | 656 ms | Slow | 79Great quality (A) · 79 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 4.3 GB | 6.0 GB | 688 ms | Slow | 81Great quality (A) · 81 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 4.8 GB | 6.0 GB | 723 ms | Slow | 83Great quality (A) · 83 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 5.9 GB | 6.0 GB | 803 ms | Slowtight fit | 84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 10.0 GB | 6.0 GB | 1.7 s | Very slowheavy RAM offload | 84Great quality (A) · 84 of 100: how capable the model is at F16, whatever it runs on. Match score 57/100 (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.