Qwen3.8-27B-DFlash2-GGUF
This repository contains GGUF conversions of incoai/Qwen3.8-27B-DFlash2, the DFlash 2 draft model for Qwen/Qwen3.8-27B. It is not a standalone language model: it runs inside a speculative decoding server and drafts tokens for the target model to verify. This repository is a mirror of incoai/Qwen3.8-27B-DFlash2-GGUF.
Params
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Context
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daily snapshots · 21 days689 K213 K
Aug 31Sep 7Sep 14Sep 20
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| Qwen3.8-27B-DFlash2-Q4_K_M.gguf | Q4_K_M | 1.1 GB | 1.8 GB | ✅ Runs comfortably |
| Qwen3.8-27B-DFlash2-Q8_0.gguf | Q8_0 | 2.1 GB | 2.8 GB | ✅ Runs comfortably |
| Qwen3.8-27B-DFlash2-BF16.gguf | GGUF | 3.9 GB | 4.7 GB | ✅ Runs comfortably |
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 run qwen3-8-27b-dflash2-gguf # pin the quantization explicitly $ ollama run qwen3-8-27b-dflash2-gguf-q4_k_m
$ huggingface-cli download z-lab/Qwen3.8-27B-DFlash2-GGUF-GGUF \
Qwen3.8-27B-DFlash2-Q4_K_M.gguf --local-dir .
$ llama-cli -m Qwen3.8-27B-DFlash2-Q4_K_M.gguf \
-c 8192 -ngl 99 -t 8 --color
$ curl -s https://aimodelscomparison.com/api/v1/models/qwen3-8-27b-dflash2-gguf
{
"hf_id": "z-lab/Qwen3.8-27B-DFlash2-GGUF",
"params_b": null,
"context_length": null,
"license": { "id": "apache-2.0", "commercial": "yes" },
"downloads_30d": 689445,
"vram_estimates": [
{ "quant": "GGUF", "gb": 4.7 },
{ "quant": "Q4_K_M", "gb": 1.8 }
],
"updated_at": "2026-08-31T01:00:23Z"
}
Specifications
- Licence
- apache-2.0
- First seen on the Hub
- 2026-08-18
- Base model
- Qwen3.8-27B
- Training datasets
- undisclosed
- Added to our catalog
- 2026-08-31
Compare with any text-generation model