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Ornith 1.5 35B A3B GGUF

Ornith 1.5 35B A3B GGUF is the GGUF-format text-generation model published in the ornith-ai/Ornith-1.5-35B-A3B-GGUF repository under the MIT license. It is the mid-size mixture-of-experts member of the Ornith-1.5 family, activating only about 3B parameters per token. The upstream Ornith-1.5 model extends Ornith-1.0 by jointly optimizing task generation, scaffold construction, and solution rollouts through an end-to-end self-improvement loop with reinforcement learning. The official model card reports benchmark comparisons against Ornith-1.0-35B-A3B, Qwen3.6-35B-A3B, Gemma-4-31B, Muse-Glimmer-30B, and Qwen3.5-397B on coding and agentic evaluations.

EstimatedRepository opened Aug 18, 2026Source checked 9/24/2026Version: 12393612
LOCALRENTED GPUOPEN WEIGHTS
Freshness 80 out of 100. Repository age: 58 days old, Aug 18, 2026. Measures age, not quality.
Popularity 86 out of 100. 3,709,734 downloads in 30 days; 512 lifetime likes. Checked Oct 15, 2026. Measures adoption, not quality.
What do these scores mean?

Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.

Freshness · release age

A new release starts at 100. The score halves every 180 days: 100 × 2^(−age in days / 180). When the release date is unavailable, a repository date is a fallback—not proof of when the model was released. Missing dates stay unscored.

Check the date source
Popularity · adoption

Downloads over the past 30 days carry 80% of the score; lifetime likes carry 20%. Both use a logarithmic scale, capped at 10 million downloads and 100,000 likes. If likes are unavailable, downloads carry all the weight. Missing download statistics stay unscored.

round(80 × min(1, log10(1 + downloads) / 7) + 20 × min(1, log10(1 + likes) / 5))

Check the statistics source
Scores as of Oct 15, 2026. Statistics checked Oct 15, 2026. Statistics are marked for refresh after 72 hours.Full scoring method

At a glance

Architecture
unknown
License
mit
Disk space
20.2 GB
Software
Ollama, llama.cpp
View the model source
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Best for

  • Text generation tasks via GGUF-compatible runtimes
  • Coding benchmark-style tasks
  • Agentic benchmark-style tasks
  • Exploring the Ornith-1.5 self-improvement methodology
  • Comparing against the listed Ornith-1.0, Qwen, Gemma, and Muse baseline models

Tradeoffs

  • Only the GGUF format and text-generation pipeline are explicitly stated; no other formats are documented
  • Approximately 3B parameters are activated per token, but full hardware requirements are not specified
  • No compatibility information is provided for specific local inference software
  • No performance claims beyond the benchmark table in the official model card are provided
  • No separate license terms for the GGUF repository are stated beyond the MIT license listed for the model

Ways to run it

Ollama · Windows, macOS, Linux

Repository-specific command in publisher documentation; confirm dependencies and hardware in the source.

ollama run hf.co/ornith-ai/Ornith-1.5-35B-A3B-GGUF
Official instructions

llama.cpp · Windows, macOS, Linux

Repository-specific command in publisher documentation; confirm dependencies and hardware in the source.

llama-server -hf ornith-ai/Ornith-1.5-35B-A3B-GGUF --port 8000 -c 262144
Official instructions

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GGUFTEXT-GENERATION

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Ornith 1.5 35B A3B GGUF: hardware, VRAM & setup | YouRunAI