0bserverx·Qwen 3.8·Qwen3_5ForCausalLM

Qwen3.8 27B Heretic Abliterated Uncensored — Hardware Requirements & GPU Compatibility

ChatFunctions

Qwen3.8 27B Heretic Abliterated Uncensored is a 26.9B-parameter open language model from 0bserverx in the Qwen 3.8 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.

1.9K downloads 3 likes262K context

Specifications

Publisher
0bserverx
Family
Qwen 3.8
Parameters
26.9B
Architecture
Qwen3_5ForCausalLM
Context Length
262,144 tokens
Vocabulary Size
248,320
Release Date
2026-09-06
License
Apache 2.0

Get Started

Run in cloud

Fits on RTX 3090 (24 GB) (7 GB headroom) · Q4_K_M

Generation speed
~36 tok/s
generation speed
Cost per 1M output tokens
$1.10
per 1M output tokens
Compare GPUs →
or

How Much VRAM Does Qwen3.8 27B Heretic Abliterated Uncensored Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q2_Kest.3.4012.2 GB
Q3_K_Mest.3.9013.9 GB
Q4_K_Mest.4.8016.9 GB
Q5_K_Mest.5.7019.9 GB
Q6_Kest.6.6022.9 GB
Q8_0est.8.0027.6 GB
BF16est.16.0054.5 GB

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 Heretic Abliterated Uncensored?

Q4_K_M · 16.9 GB

Qwen3.8 27B Heretic Abliterated Uncensored (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 13.9 GB, bringing total usage to 30.8 GB. 8 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.

Which Devices Can Run Qwen3.8 27B Heretic Abliterated Uncensored?

Q4_K_M · 16.9 GB

41 devices with unified memory can run Qwen3.8 27B Heretic Abliterated Uncensored, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).

Runs great

— Plenty of headroom

Related Models

Frequently Asked Questions

How much VRAM does Qwen3.8 27B Heretic Abliterated Uncensored need?

Qwen3.8 27B Heretic Abliterated Uncensored requires 16.9 GB of VRAM at Q4_K_M, or 54.5 GB at BF16. Full 262K context adds up to 13.9 GB (30.8 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)

Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.

KV Cache + Overhead ≈ 14.7 GB (at full 262K context)

VRAM usage by quantization

16.9 GB
30.8 GB

Learn more about VRAM estimation →

Can NVIDIA GeForce RTX 4090 run Qwen3.8 27B Heretic Abliterated Uncensored?

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 Qwen3.8 27B Heretic Abliterated Uncensored?

For Qwen3.8 27B Heretic Abliterated Uncensored, Q4_K_M (16.9 GB) offers the best balance of quality and VRAM usage. Q5_K_M (19.9 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 12.2 GB.

VRAM requirement by quantization

Q2_K
12.2 GB
Q4_K_M ★
16.9 GB
Q5_K_M
19.9 GB
Q6_K
22.9 GB
Q8_0
27.6 GB
BF16
54.5 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run Qwen3.8 27B Heretic Abliterated Uncensored on a Mac?

Yes, but only at lower quantizations. The smallest Mac that can run Qwen3.8 27B Heretic Abliterated Uncensored is Mac Mini M4 (16 GB) at Q2_K; 29 of the 39 Macs we list can run it at some quantization. For Q4_K_M (16.9 GB) you need a Mac with more unified memory.

Can I run Qwen3.8 27B Heretic Abliterated Uncensored locally?

Yes — Qwen3.8 27B Heretic Abliterated Uncensored 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 Qwen3.8 27B Heretic Abliterated Uncensored?

At Q4_K_M, Qwen3.8 27B Heretic Abliterated Uncensored can reach ~284 tok/s on AMD Instinct MI350X. 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: NVIDIA B200 → 8000 ÷ 16.9 × 0.65 = ~308 tok/s

Estimated speed at Q4_K_M (16.9 GB)

~308 tok/s
~39 tok/s
~308 tok/s
~284 tok/s

Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.

Learn more about tok/s estimation →

What's the download size of Qwen3.8 27B Heretic Abliterated Uncensored?

At Q4_K_M, the download is about 16.14 GB. The full-precision BF16 version is 53.79 GB. The smallest option (Q2_K) is 11.43 GB.

Which GPUs can run Qwen3.8 27B Heretic Abliterated Uncensored?

8 consumer GPUs can run Qwen3.8 27B Heretic Abliterated Uncensored 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 Qwen3.8 27B Heretic Abliterated Uncensored?

41 devices with unified memory can run Qwen3.8 27B Heretic Abliterated Uncensored at Q4_K_M (16.9 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.