Ornith-1.0-35B-GGUF
Aloha! 🌺 Today, we are releasing Ornith-1.0, a self-improving family of open-source models for agentic coding.
Params
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Context
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Downloads 30d
3.8 M
Likes
1,012
Download history
tracking started — chart appears after 7 days of snapshots (1 recorded)3.8 M downloads in the last 30 days
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 |
|---|---|---|---|---|
| ornith-1.0-35b-Q4_K_M.gguf | Q4_K_M | 21.2 GB | 23.8 GB | ⚠️ Tight — reduce context |
| ornith-1.0-35b-Q5_K_M.gguf | Q5_K_M | 24.7 GB | 27.7 GB | ❌ Won’t fit |
| ornith-1.0-35b-Q6_K.gguf | Q6_K | 28.5 GB | 31.9 GB | ❌ Won’t fit |
| ornith-1.0-35b-Q8_0.gguf | Q8_0 | 36.9 GB | 41.1 GB | ❌ Won’t fit |
| ornith-1.0-35b-bf16.gguf | GGUF | 69.4 GB | 76.8 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 ornith-1-0-35b-gguf-ornith-ai # pin the quantization explicitly $ ollama run ornith-1-0-35b-gguf-ornith-ai-q4_k_m
$ huggingface-cli download ornith-ai/Ornith-1.0-35B-GGUF-GGUF \
ornith-1.0-35b-Q4_K_M.gguf --local-dir .
$ llama-cli -m ornith-1.0-35b-Q4_K_M.gguf \
-c 8192 -ngl 99 -t 8 --color
$ curl -s https://aimodelscomparison.com/api/v1/models/ornith-1-0-35b-gguf-ornith-ai
{
"hf_id": "ornith-ai/Ornith-1.0-35B-GGUF",
"params_b": null,
"context_length": null,
"license": { "id": "mit", "commercial": "yes" },
"downloads_30d": 3755106,
"vram_estimates": [
{ "quant": "Q4_K_M", "gb": 23.8 },
{ "quant": "Q5_K_M", "gb": 27.7 }
],
"updated_at": "2026-08-06T01:00:12Z"
}
Specifications
- Licence
- mit
- First seen on the Hub
- 2026-06-25
- Training datasets
- undisclosed
- Added to our catalog
- 2026-08-06
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