Deep Reinforce Ornith 35B
Deep Reinforce's flagship 35B self-improving agentic-coding model (MIT) with 256K context — state-of-the-art open-source coding for its size.
Ornith 35B is an open-weight text model from Deep Reinforce. It takes a text prompt and replies with generated text. Its context window handles up to 262K input tokens. It runs entirely on your own hardware through Ollama: no API key and no per-use fees.
- Released
- Jun 2026
- Pricing
- Free, runs on your hardware
- Context window
- 262K in
Samples
Generated with Ornith 35B via Ollama. The same three prompts run against every text model in the catalog, shown verbatim, so the only thing that changes between two models’ answers is the model.
Explain what an API is to someone who has never written code. Do not use a restaurant or waiter analogy. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 50 words.
An API is a rulebook that lets two computer programs exchange information. Like a universal power plug connecting any device to any outlet, it lets different software safely request and share data. It handles the translation so programs work together without reading private code.
A two-person startup is deciding whether to build their own user authentication or use a hosted provider. Give them a clear recommendation, then the single strongest argument against your own recommendation. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 150 words.
Use a hosted authentication provider. As a two-person team, your security expertise and time are your scarcest resources. Building auth from scratch requires implementing password hashing, session management, OAuth flows, multi-factor authentication, and compliance with ever-changing privacy regulations. A single misstep can lead to a breach that destroys your startup before it launches. Hosted providers distribute that risk and let you ship your actual product faster. The strongest argument against this choice is vendor lock-in. Migrating users away from a third-party auth system later is notoriously painful, expensive, and risky. As you scale, per-seat pricing can also outpace the cost of maintaining your own solution, and you lose fine-grained control over user data handling, which may conflict with strict privacy requirements or regulatory environments.
Deep Reinforce
Deep Reinforce builds the Ornith family — self-improving open-weight (MIT) models for agentic coding, tuned with reinforcement learning on coding and terminal benchmarks.
deep-reinforce.com ↗Deep Reinforce's 9B self-improving agentic-coding model (MIT) with 256K context and native tool use.
Deep Reinforce's 9B self-improving model (MIT) with 256K context, image input, and native tool use, tuned for reasoning, coding, and agentic work.
Deep Reinforce's 35B MoE self-improving model (MIT) with 256K context, image input, and native tool use, strong across reasoning, coding, and agentic tasks.
Deep Reinforce's 122B MoE self-improving model (MIT) with 256K context, image input, and native tool use, the largest Ornith 1.5 size that runs on a single high-memory machine.