Family Qwen · 28B parameters

Qwen 3.8 27B Obliterated Mythos Agentic

Agentic “abliterated” finetune of Qwen 3.8 27B: uncensored dense 28B, 262k context, ~16 GB VRAM in Q4. Reasoning + code (Aider/OpenCode), without guardrails.

🇨🇳 medismera·License Apache 2.0·Context 256k tokens·Output 2026-09-07·Fits within the 128 GB of the GIGABYTE AI TOP ATOM← Catalog

01What it can do

Strengths
  • Versatile, multilingual Dense 28B
  • 262k native context
  • Focused on agents and code (Aider / OpenCode)
  • Unfiltered responses
  • Permissive Apache 2.0 license
Limitations to know
  • —~16 GB VRAM in Q4: 16–24 GB GPU recommended
  • —Abliteration = possible loss of alignment and safety
  • —No Ollama tag — install via Hugging Face
Architecture
Dense Transformer · 28B parameters · 262k context (tested in production at 128k) · agentic “abliterated” variant of Qwen 3.8 27B
Training
Community finetune (medismera) of Qwen 3.8 27B: abliteration (removal of refusals) aimed at “Mythos-Class” agentic use. Official base Qwen; training details not published.
Ideal for
Autonomous agentsCode / reasoningUnfiltered chat

04Install

Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.

$# HuggingFace : medismera/Qwen3.8-27B-OBLITERATED-Mythos-Class-Agentic
⚠
First download: between 2 and 40 GB depending on the selected quantization. Plan for sufficient disk space; a stable connection is recommended. Subsequent launches are instant.

02Required memory

Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.

Q4_K_M
The lightest, ~5% loss
16 GB
Q5_K_M
Good quality/size compromise
20 GB
Q8_0
Nearly indistinguishable from FP16
30 GB
FP16
Full precision — server use
56 GB
Fallback CPU · If you don't have a GPU, allow 36 GB of RAM minimum to run this model at reduced speed.

What hardware do you need for Qwen 3.8 27B Obliterated Mythos Agentic?

To run Qwen 3.8 27B Obliterated Mythos Agentic locally with Q4 quantization, you need about 16 GB of VRAM. An option to compare: GMKtec EVO-X2 64GB / 1TB (Ryzen AI Max+ 395) — leave some headroom for the system and context; check engine compatibility with the GPU.

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On the go: Qwen 3.8 27B Obliterated Mythos Agentic also runs on a RTX laptop PC (16 GB of VRAM) →

03Expected speed

Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.

Entry-level
~9t/s
GTX 1650, RX 6600, MBA M2 8GB
Mid-range
~14t/s
RTX 4060, 4070, MBP M3 Pro
High-end
~22t/s
RTX 4090, M4 Max, Radeon 7900