Qwen3 06B Qat Test — Hardware Requirements & GPU Compatibility
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Qwen3 06B Qat Test is a 6B-parameter open language model from Thomaschtl in the Qwen 3 family. At BF16 it needs about 13.20 GB of VRAM — see which GPUs and Macs can run it below.
1 likesSpecifications
- Publisher
- Thomaschtl
- Family
- Qwen 3
- Parameters
- 6B
- Release Date
- 2025-06-03
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Qwen3 06B Qat Test Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16est. | 16.00 | 13.2 GB | — | 12.00 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Qwen3 06B Qat Test?
BF16 · 13.2 GBQwen3 06B Qat Test (BF16) requires 13.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 18+ GB is recommended. 26 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 5080.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Qwen3 06B Qat Test?
BF16 · 13.2 GB47 devices with unified memory can run Qwen3 06B Qat Test, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 (16 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Qwen3 06B Qat Test need?
Qwen3 06B Qat Test requires 13.2 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 6B × 16 bits ÷ 8 = 12 GB
KV Cache + Overhead ≈ 1.2 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF1613.2 GB- Can I run Qwen3 06B Qat Test on a Mac?
Qwen3 06B Qat Test requires at least 13.2 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Qwen3 06B Qat Test locally?
Yes — Qwen3 06B Qat Test can run locally on consumer hardware. At BF16 quantization it needs 13.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen3 06B Qat Test?
At BF16, Qwen3 06B Qat Test can reach ~364 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~50 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 13.2 × 0.65 = ~394 tok/s
Estimated speed at BF16 (13.2 GB)
~394 tok/s~50 tok/s~394 tok/s~364 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen3 06B Qat Test?
At BF16, the download is about 12.00 GB.
- Which GPUs can run Qwen3 06B Qat Test?
26 consumer GPUs can run Qwen3 06B Qat Test at BF16 (13.2 GB). Top options include AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090, AMD Radeon RX 6800. 8 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Qwen3 06B Qat Test?
49 devices with unified memory can run Qwen3 06B Qat Test at BF16 (13.2 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.