Ornith 1.5
Version: 1.5
By DeepReinforce
Released: 2026-08-19
DeepReinforce's MIT-licensed, self-improving open-weights model family, released 19 August 2026 in three sizes (9B dense, 35B MoE, 397B MoE flagship). Its training loop has the model generate its own tasks, scaffolds and reinforcement-learning rollouts, and it posts benchmark scores that match or beat Claude Opus 4.8 on some agentic and coding tasks while trailing it on others.
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Optimized performance ensures quick results without compromising on quality.
Purpose-Built
Specifically designed for llms tasks and workflows.
DeepReinforce Model Timeline
Specifications
AI Evaluation
A genuinely free, MIT-licensed open-weights family with a novel self-generated training curriculum, scoring competitively with Claude Opus 4.8 on some agentic and coding benchmarks, though every figure is self-reported and there's no published safety evaluation yet.
Pros
- Free, MIT-licensed across all three sizes with no revenue threshold
- Novel self-improvement loop with explicit validity, difficulty and novelty gating
- 9B model runs on a single consumer GPU or phone, an accessible entry point
Cons
- All benchmark figures are DeepReinforce's own, not yet independently reproduced
- No published system card, CBRN evaluation or safety documentation
- 397B flagship needs multi-GPU, datacentre-class hardware to run at useful speed
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