Bonsai-27B-gguf
Prism ML Website Whitepaper Demo & Examples Discord
Params
—
Context
—
Downloads 30d
440 K
Likes
867
Download history
daily snapshots · 56 days
▲ 593 K in the last 30 days (57.4%)
931 K416 K
Aug 23Sep 2Sep 12Sep 21
2.7 M416 K
Jul 28Aug 15Sep 3Sep 21
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 |
|---|---|---|---|---|
| Bonsai-27B-mmproj-Q8_0.gguf | Q8_0 | 0.6 GB | 1.2 GB | ✅ Runs comfortably |
| Bonsai-27B-dspark-Q4_1.gguf | Q4_1 | 1.8 GB | 2.5 GB | ✅ Runs comfortably |
| Bonsai-27B-Q1_0.gguf | Q1_0 | 3.8 GB | 4.7 GB | ✅ Runs comfortably |
| Bonsai-27B-F16.gguf | GGUF | 53.8 GB | 59.7 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 bonsai-27b-gguf # pin the quantization explicitly $ ollama run bonsai-27b-gguf-q4_1
$ huggingface-cli download prism-ml/Bonsai-27B-gguf-GGUF \
Bonsai-27B-dspark-Q4_1.gguf --local-dir .
$ llama-cli -m Bonsai-27B-dspark-Q4_1.gguf \
-c 8192 -ngl 99 -t 8 --color
$ curl -s https://aimodelscomparison.com/api/v1/models/bonsai-27b-gguf
{
"hf_id": "prism-ml/Bonsai-27B-gguf",
"params_b": null,
"context_length": null,
"license": { "id": "apache-2.0", "commercial": "yes" },
"downloads_30d": 439865,
"vram_estimates": [
{ "quant": "GGUF", "gb": 59.7 },
{ "quant": "Q1_0", "gb": 4.7 }
],
"updated_at": "2026-07-28T17:07:50Z"
}
Specifications
- Licence
- apache-2.0
- First seen on the Hub
- 2026-07-04
- Base model
- Qwen3.6-27B
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Compare with any text-generation model