Qwen3.8 27B Uncensored — Hardware Requirements & GPU Compatibility
VisionFunctionsReasoning
Qwen3.8 27B Uncensored is a 27.8B-parameter open language model from orcarouter in the Qwen 3.8 family. At Q4_K_M it needs about 18.34 GB of VRAM — see which GPUs and Macs can run it below.
67.0K downloads
232 likesSpecifications
- Publisher
- orcarouter
- Family
- Qwen 3.8
- Parameters
- 27.8B
- Release Date
- 2026-08-18
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Qwen3.8 27B Uncensored Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 13.0 GB | — | 11.81 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 14.9 GB | — | 13.54 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 18.3 GB | — | 16.67 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 21.8 GB | — | 19.79 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 25.2 GB | — | 22.92 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 30.6 GB | — | 27.78 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 61.1 GB | — | 55.56 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 Qwen3.8 27B Uncensored?
Q4_K_M · 18.3 GBQwen3.8 27B Uncensored (Q4_K_M) requires 18.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 24+ GB is recommended. 8 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Qwen3.8 27B Uncensored?
Q4_K_M · 18.3 GB41 devices with unified memory can run Qwen3.8 27B Uncensored, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Qwen3.8 27B Uncensored need?
Qwen3.8 27B Uncensored requires 18.3 GB of VRAM at Q4_K_M, or 61.1 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 27.8B × 4.8 bits ÷ 8 = 16.7 GB
KV Cache + Overhead ≈ 1.6 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M18.3 GB- Can NVIDIA GeForce RTX 4090 run Qwen3.8 27B Uncensored?
Yes, at Q5_K_M (21.8 GB) or lower. Higher quantizations like Q6_K (25.2 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Qwen3.8 27B Uncensored?
For Qwen3.8 27B Uncensored, Q4_K_M (18.3 GB) offers the best balance of quality and VRAM usage. Q5_K_M (21.8 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 13.0 GB.
VRAM requirement by quantization
Q2_K13.0 GBQ4_K_M ★18.3 GBQ5_K_M21.8 GBQ6_K25.2 GBQ8_030.6 GBBF1661.1 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen3.8 27B Uncensored on a Mac?
Qwen3.8 27B Uncensored requires at least 13.0 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 Qwen3.8 27B Uncensored locally?
Yes — Qwen3.8 27B Uncensored can run locally on consumer hardware. At Q4_K_M quantization it needs 18.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen3.8 27B Uncensored?
At Q4_K_M, Qwen3.8 27B Uncensored can reach ~262 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~36 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 ÷ 18.3 × 0.65 = ~284 tok/s
Estimated speed at Q4_K_M (18.3 GB)
~284 tok/s~36 tok/s~284 tok/s~262 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen3.8 27B Uncensored?
At Q4_K_M, the download is about 16.67 GB. The full-precision BF16 version is 55.56 GB. The smallest option (Q2_K) is 11.81 GB.
- Which GPUs can run Qwen3.8 27B Uncensored?
8 consumer GPUs can run Qwen3.8 27B Uncensored at Q4_K_M (18.3 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 Qwen3.8 27B Uncensored?
41 devices with unified memory can run Qwen3.8 27B Uncensored at Q4_K_M (18.3 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.