empero-ai / text-generation Open weights updated 1 month ago

Qwen3.8-35B-A3B-Distill-GGUF

GGUF quantizations of empero-ai/Qwen3.8-35B-A3B-Distill — a distillation of the Qwen3.8 frontier models into the Qwen3.6-35B-A3B Mixture-of-Experts architecture — for llama.cpp, Ollama, LM Studio, Jan, KoboldCpp, and other stock GGUF runtimes.

Params
35.0 B
Context
—
Downloads 30d
1.2 M
Likes
239
Commercial use: allowed apache-2.0 Not gated GGUF 1 languages View on Hugging Face ↗

Download history

daily snapshots · 28 days
1.2 M222 K
Sep 27Oct 6Oct 15Oct 24

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

FileQuantSizeEst. VRAMVerdict on RTX 4090 · 24 GB
Qwen3.8-35B-A3B-IQ2_M.gguf IQ2_M 12.6 GB 19.6 GB ✅ Runs comfortably
Qwen3.8-35B-A3B-Q2_K.gguf Q2_K 13.8 GB 21.0 GB ⚠️ Tight — reduce context
Qwen3.8-35B-A3B-IQ3_M.gguf IQ3_M 16.3 GB 23.7 GB ⚠️ Tight — reduce context
Qwen3.8-35B-A3B-Q3_K_M.gguf Q3_K_M 17.7 GB 25.2 GB ❌ Won’t fit
Qwen3.8-35B-A3B-IQ4_XS.gguf IQ4_XS 19.6 GB 27.3 GB ❌ Won’t fit
Qwen3.8-35B-A3B-Q4_K_M.gguf Q4_K_M 21.7 GB 29.6 GB ❌ Won’t fit
Qwen3.8-35B-A3B-Q5_K_M.gguf Q5_K_M 25.3 GB 33.6 GB ❌ Won’t fit
Qwen3.8-35B-A3B-BF16.gguf GGUF 71.1 GB 83.9 GB ❌ Won’t fit
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Run it

copy-paste, exact tags checked against the Hub
~ · ollama · Q4_K_M
$ ollama run qwen3-8-35b-a3b-distill-gguf

# pin the quantization explicitly
$ ollama run qwen3-8-35b-a3b-distill-gguf-q4_k_m
est. VRAM 29.6 GBon RTX 4090 · 24 GBJSON API →

Specifications

Parameters
35.0 B
Licence
apache-2.0
First seen on the Hub
2026-09-16
Training datasets
undisclosed
Added to our catalog
2026-09-27
Compare with any text-generation model