unsloth / text-generation Open weights updated 2 weeks ago

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
593 K
Likes
98
Commercial use: allowed mit Not gated GGUF View on Hugging Face ↗

Download history

daily snapshots · 12 days
593 K161 K
Oct 30Nov 3Nov 7Nov 10

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

FileQuantSizeEst. VRAMVerdict on RTX 4090 · 24 GB
Ornith-1.5-122B-UD-IQ1_M.gguf IQ1_M 40.4 GB 63.2 GB ❌ Won’t fit
Ornith-1.5-122B-UD-IQ2_XXS.gguf IQ2_XXS 42.0 GB 65.0 GB ❌ Won’t fit
Ornith-1.5-122B-UD-Q2_K_XL.gguf Q2_K_XL 44.5 GB 67.8 GB ❌ Won’t fit
Ornith-1.5-122B-BF16-00006-of-00007.gguf GGUF 48.6 GB 72.3 GB ❌ Won’t fit
Ornith-1.5-122B-UD-IQ3_XXS.gguf IQ3_XXS 49.5 GB 73.3 GB ❌ Won’t fit
Ornith-1.5-122B-UD-Q3_K_XL-00002-of-00003.gguf Q3_K_XL 49.8 GB 73.6 GB ❌ Won’t fit
Ornith-1.5-122B-Q8_0-00003-of-00004.gguf Q8 49.9 GB 73.7 GB ❌ Won’t fit
Ornith-1.5-122B-UD-Q4_K_XL-00002-of-00003.gguf Q4_K_XL 50.0 GB 73.8 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 · Q4_K_XL
$ ollama run ornith-1-5-122b-gguf-unsloth

# pin the quantization explicitly
$ ollama run ornith-1-5-122b-gguf-unsloth-q4_k_xl
est. VRAM 73.8 GBon RTX 4090 · 24 GBJSON API →

Specifications

Parameters
122.0 B
Licence
mit
First seen on the Hub
2026-10-20
Training datasets
undisclosed
Added to our catalog
2026-10-30
Compare with any text-generation model