qwen3.8-flash-next-gguf
Self-contained GGUFs for DwarfStar, with original BF16 n-grams read directly from disk. Keep the file on a local SSD. No n-gram sidecar is needed. MTP weights are included; enable them with --mtp. Requires DwarfStar's native BF16 n-gram reader. Older versions expecting --ple cannot load these files.
Params
180.0 B
Context
—
Downloads 30d
251 K
Likes
15
Download history
daily snapshots · 35 days
▲ 61 K in the last 30 days (32.1%)
280 K180 K
Oct 12Oct 22Nov 1Nov 10
280 K180 K
Oct 7Oct 18Oct 30Nov 10
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-Flash-Next-Q2.gguf | Q2 | 147.2 GB | 189.4 GB | ❌ Won’t fit |
| Qwen3.8-Flash-Next-Q4.gguf | Q4 | 177.3 GB | 222.5 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 run qwen3-8-flash-next-gguf-antirez # pin the quantization explicitly $ ollama run qwen3-8-flash-next-gguf-antirez-q4
$ huggingface-cli download antirez/qwen3.8-flash-next-gguf-GGUF \
Qwen3.8-Flash-Next-Q4.gguf --local-dir .
$ llama-cli -m Qwen3.8-Flash-Next-Q4.gguf \
-c 8192 -ngl 99 -t 8 --color
$ curl -s https://aimodelscomparison.com/api/v1/models/qwen3-8-flash-next-gguf-antirez
{
"hf_id": "antirez/qwen3.8-flash-next-gguf",
"params_b": 180.00,
"context_length": null,
"license": { "id": "other", "commercial": "unknown" },
"downloads_30d": 251356,
"vram_estimates": [
{ "quant": "Q2", "gb": 189.4 },
{ "quant": "Q4", "gb": 222.5 }
],
"updated_at": "2026-10-07T01:00:23Z"
}
Specifications
- Parameters
- 180.0 B
- Licence
- other
- First seen on the Hub
- 2026-09-14
- Base model
- Qwen3.8-Flash-Next
- Training datasets
- undisclosed
- Added to our catalog
- 2026-10-07
Family
Base model and the most-downloaded derivatives in the catalog.
Compare with any text-generation model