Qwen3.6 35B A3B DFlash — Hardware Requirements & GPU Compatibility
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Qwen3.6 35B A3B DFlash is a 474M-parameter open language model from z-lab in the Qwen family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 0.60 GB of VRAM — see which GPUs and Macs can run it below.
73.8K downloads
236 likesSpecifications
- Publisher
- z-lab
- Family
- Qwen
- Parameters
- 474M
- Architecture
- DFlashDraftModel
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-04-26
- License
- MIT
Get Started
HuggingFace
How Much VRAM Does Qwen3.6 35B A3B DFlash Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| IQ4_XS | 4.30 | 0.6 GB | 2.7 GB | 0.25 GB | Importance-weighted 4-bit, compact |
| Q4_K_M | 4.80 | 0.6 GB | 2.7 GB | 0.28 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 0.7 GB | 2.8 GB | 0.34 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 0.7 GB | 2.8 GB | 0.39 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 0.8 GB | 2.9 GB | 0.47 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Qwen3.6 35B A3B DFlash?
Q4_K_M · 0.6 GBQwen3.6 35B A3B DFlash (Q4_K_M) requires 0.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 1+ GB is recommended. Using the full 262K context window can add up to 2.1 GB, bringing total usage to 2.7 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Qwen3.6 35B A3B DFlash?
Q4_K_M · 0.6 GB33 devices with unified memory can run Qwen3.6 35B A3B DFlash, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Derivatives (1)
Frequently Asked Questions
- How much VRAM does Qwen3.6 35B A3B DFlash need?
Qwen3.6 35B A3B DFlash requires 0.6 GB of VRAM at Q4_K_M, or 0.8 GB at Q8_0. Full 262K context adds up to 2.1 GB (2.7 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 474M × 4.8 bits ÷ 8 = 0.3 GB
KV Cache + Overhead ≈ 0.3 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 2.4 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M0.6 GBQ4_K_M + full context2.7 GB- What's the best quantization for Qwen3.6 35B A3B DFlash?
For Qwen3.6 35B A3B DFlash, Q4_K_M (0.6 GB) offers the best balance of quality and VRAM usage. Q5_K_M (0.7 GB) provides better quality if you have the VRAM. The smallest option is IQ4_XS at 0.6 GB.
VRAM requirement by quantization
IQ4_XS0.6 GBQ4_K_M ★0.6 GBQ5_K_M0.7 GBQ6_K0.7 GBQ8_00.8 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen3.6 35B A3B DFlash on a Mac?
Qwen3.6 35B A3B DFlash requires at least 0.6 GB at IQ4_XS, 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 Qwen3.6 35B A3B DFlash locally?
Yes — Qwen3.6 35B A3B DFlash can run locally on consumer hardware. At Q4_K_M quantization it needs 0.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen3.6 35B A3B DFlash?
At Q4_K_M, Qwen3.6 35B A3B DFlash can reach ~4858 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~1092 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 0.6 × 0.55 = ~4858 tok/s
Estimated speed at Q4_K_M (0.6 GB)
~4858 tok/s~1092 tok/s~3631 tok/s~3004 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen3.6 35B A3B DFlash?
At Q4_K_M, the download is about 0.28 GB. The full-precision Q8_0 version is 0.47 GB. The smallest option (IQ4_XS) is 0.25 GB.
- Which GPUs can run Qwen3.6 35B A3B DFlash?
35 consumer GPUs can run Qwen3.6 35B A3B DFlash at Q4_K_M (0.6 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 35 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Qwen3.6 35B A3B DFlash?
33 devices with unified memory can run Qwen3.6 35B A3B DFlash at Q4_K_M (0.6 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.