Ternary-Bonsai-27B-gguf
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Params
—
Context
—
Downloads 30d
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Download history
daily snapshots · 10 days761 K665 K
Jul 28Jul 31Aug 3Aug 6
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 |
|---|---|---|---|---|
| Ternary-Bonsai-27B-mmproj-Q8_0.gguf | Q8_0 | 0.6 GB | 1.2 GB | ✅ Runs comfortably |
| Ternary-Bonsai-27B-dspark-Q4_1.gguf | Q4_1 | 1.9 GB | 2.6 GB | ✅ Runs comfortably |
| Ternary-Bonsai-27B-PQ2_0.gguf | Q2_0 | 7.2 GB | 8.4 GB | ✅ Runs comfortably |
| Ternary-Bonsai-27B-Q2_g64.gguf | Q2_G64 | 7.6 GB | 8.8 GB | ✅ Runs comfortably |
| Ternary-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 ternary-bonsai-27b-gguf # pin the quantization explicitly $ ollama run ternary-bonsai-27b-gguf-q4_1
$ huggingface-cli download prism-ml/Ternary-Bonsai-27B-gguf-GGUF \
Ternary-Bonsai-27B-dspark-Q4_1.gguf --local-dir .
$ llama-cli -m Ternary-Bonsai-27B-dspark-Q4_1.gguf \
-c 8192 -ngl 99 -t 8 --color
$ curl -s https://aimodelscomparison.com/api/v1/models/ternary-bonsai-27b-gguf
{
"hf_id": "prism-ml/Ternary-Bonsai-27B-gguf",
"params_b": null,
"context_length": null,
"license": { "id": "apache-2.0", "commercial": "yes" },
"downloads_30d": 761269,
"vram_estimates": [
{ "quant": "GGUF", "gb": 59.7 },
{ "quant": "Q2_0", "gb": 8.4 }
],
"updated_at": "2026-07-28T18:04:22Z"
}
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
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