Ornith-1.5-122B-GGUF
Chirp Chirp! 🐦 We are introducing Ornith-1.5, a major step toward building foundation models through end-to-end self-improvement.
Params
122.0 B
Context
—
Downloads 30d
871 K
Likes
55
Download history
daily snapshots · 16 days871 K153 K
Oct 26Oct 31Nov 5Nov 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 |
|---|---|---|---|---|
| Ornith-1.5-122B-Q4_K_M.gguf | Q4_K_M | 75.8 GB | 102.2 GB | ❌ Won’t fit |
| Ornith-1.5-122B-Q5_K_M.gguf | Q5_K_M | 88.7 GB | 116.4 GB | ❌ Won’t fit |
| Ornith-1.5-122B-Q6_K.gguf | Q6_K | 102.4 GB | 131.4 GB | ❌ Won’t fit |
| Ornith-1.5-122B-Q8_0.gguf | Q8_0 | 132.6 GB | 164.6 GB | ❌ Won’t fit |
| Ornith-1.5-122B-BF16.gguf | GGUF | 249.4 GB | 293.1 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-1-5-122b-gguf # pin the quantization explicitly $ ollama run ornith-1-5-122b-gguf-q4_k_m
$ huggingface-cli download ornith-ai/Ornith-1.5-122B-GGUF-GGUF \
Ornith-1.5-122B-Q4_K_M.gguf --local-dir .
$ llama-cli -m Ornith-1.5-122B-Q4_K_M.gguf \
-c 8192 -ngl 99 -t 8 --color
$ curl -s https://aimodelscomparison.com/api/v1/models/ornith-1-5-122b-gguf
{
"hf_id": "ornith-ai/Ornith-1.5-122B-GGUF",
"params_b": 122.00,
"context_length": null,
"license": { "id": "mit", "commercial": "yes" },
"downloads_30d": 870881,
"vram_estimates": [
{ "quant": "GGUF", "gb": 293.1 },
{ "quant": "Q4_K_M", "gb": 102.2 }
],
"updated_at": "2026-10-26T01:00:16Z"
}
Specifications
- Parameters
- 122.0 B
- Licence
- mit
- First seen on the Hub
- 2026-10-20
- Training datasets
- undisclosed
- Added to our catalog
- 2026-10-26
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