Qwen3.6 27B MTPLX Optimized — Hardware Requirements & GPU Compatibility
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Qwen3.6 27B MTPLX Optimized is a 26.9B-parameter open language model from Youssofal in the Qwen family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 16.88 GB of VRAM — see which GPUs and Macs can run it below.
5.4K downloads
7 likesSpecifications
- Publisher
- Youssofal
- Family
- Qwen
- Parameters
- 26.9B
- Architecture
- Qwen3_5ForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-05-04
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Qwen3.6 27B MTPLX Optimized Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 12.2 GB | 69 GB | 11.43 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 12.5 GB | 69.3 GB | 11.77 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 13.9 GB | 70.7 GB | 13.11 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 16.9 GB | 73.7 GB | 16.14 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 19.9 GB | 76.7 GB | 19.16 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 22.9 GB | 79.8 GB | 22.19 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 27.6 GB | 84.5 GB | 26.90 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Qwen3.6 27B MTPLX Optimized?
Q4_K_M · 16.9 GBQwen3.6 27B MTPLX Optimized (Q4_K_M) requires 16.9 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 22+ GB is recommended. Using the full 262K context window can add up to 56.8 GB, bringing total usage to 73.7 GB. 6 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Qwen3.6 27B MTPLX Optimized?
Q4_K_M · 16.9 GB21 devices with unified memory can run Qwen3.6 27B MTPLX Optimized, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Qwen3.6 27B MTPLX Optimized need?
Qwen3.6 27B MTPLX Optimized requires 16.9 GB of VRAM at Q4_K_M, or 27.6 GB at Q8_0. Full 262K context adds up to 56.8 GB (73.7 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 26.9B × 4.8 bits ÷ 8 = 16.1 GB
KV Cache + Overhead ≈ 0.8 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 57.6 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M16.9 GBQ4_K_M + full context73.7 GB- Can NVIDIA GeForce RTX 4090 run Qwen3.6 27B MTPLX Optimized?
Yes, at Q6_K (22.9 GB) or lower. Higher quantizations like Q8_0 (27.6 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Qwen3.6 27B MTPLX Optimized?
For Qwen3.6 27B MTPLX Optimized, Q4_K_M (16.9 GB) offers the best balance of quality and VRAM usage. Q5_K_S (19.2 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 12.2 GB.
VRAM requirement by quantization
Q2_K12.2 GBQ3_K_L14.5 GBQ4_K_S15.9 GBQ4_K_M ★16.9 GBQ5_K_M19.9 GBQ8_027.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen3.6 27B MTPLX Optimized on a Mac?
Qwen3.6 27B MTPLX Optimized requires at least 12.2 GB at Q2_K, 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 27B MTPLX Optimized locally?
Yes — Qwen3.6 27B MTPLX Optimized can run locally on consumer hardware. At Q4_K_M quantization it needs 16.9 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen3.6 27B MTPLX Optimized?
At Q4_K_M, Qwen3.6 27B MTPLX Optimized can reach ~173 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~39 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 ÷ 16.9 × 0.55 = ~173 tok/s
Estimated speed at Q4_K_M (16.9 GB)
~173 tok/s~39 tok/s~129 tok/s~107 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 27B MTPLX Optimized?
At Q4_K_M, the download is about 16.14 GB. The full-precision Q8_0 version is 26.90 GB. The smallest option (Q2_K) is 11.43 GB.
- Which GPUs can run Qwen3.6 27B MTPLX Optimized?
6 consumer GPUs can run Qwen3.6 27B MTPLX Optimized at Q4_K_M (16.9 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX. 1 GPU have plenty of headroom for comfortable inference.
- Which devices can run Qwen3.6 27B MTPLX Optimized?
21 devices with unified memory can run Qwen3.6 27B MTPLX Optimized at Q4_K_M (16.9 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.