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DeepReinforce

Ornith 1.0

Ornith 1.0 is DeepReinforce's self-improving open-source model family for agentic coding. The Hugging Face organization and model cards list 9B-Dense, 31B-Dense, 35B-MoE and 397B-MoE positioning, with public 9B, 35B and 397B checkpoints plus GGUF and FP8 variants. The cards say the models are post-trained on top of Gemma 4 and Qwen 3.5, use reinforcement learning to optimize both solution rollouts and the scaffold that drives those rollouts, and target coding-agent benchmarks such as Terminal-Bench 2.1, SWE-Bench, NL2Repo and OpenClaw / ClawEval. The model cards document reasoning-model behavior, OpenAI-compatible serving through vLLM or SGLang with Qwen-style reasoning and tool-call parsers, Transformers loading, 262K context serving examples for 9B/35B/397B, MIT licensing, and globally accessible weights.

Globally availableFull English UIPublic APIFree

Editorial verdict

Best for

Teams evaluating open agentic-coding models for self-hosted coding agents, terminal automation, SWE-Bench workflows and long-context tool use.

Avoid if

Avoid it if you need a polished hosted coding IDE, managed team billing or a small model that runs comfortably without GPU planning.

Why it matters

Ornith 1.0 belongs in AI Coding because its public model cards and collection position it around agentic coding benchmarks and coding-agent deployment.

Trust: 5/5 sources verified, recently checkedCoverage: 100/100

Pricing

MIT open weights on Hugging Face; self-hosted inference costs depend on model size and quantization

Payment

Hugging Face model download, Transformers, vLLM, SGLang, GGUF local inference

Commercial use

Commercial use should follow the current product, API, model license and billing terms.

Privacy

Review prompt, file, media upload, retention and training-use terms before sensitive workloads.

Use-case fit

Self-hosted coding agent backend

Strong

Serve Ornith through vLLM or SGLang with reasoning and tool-call parsers for coding-agent experiments.

Coding benchmark reproduction

Strong

Reproduce Terminal-Bench, SWE-Bench, NL2Repo, SWE Atlas or ClawEval results before selecting a model size.

Local and compressed deployment

Medium

Evaluate 9B or GGUF variants for lighter experiments, and FP8 variants when compressed large-model serving matters.

Global user checklist

RegistrationConfirmedThe DeepReinforce Hugging Face organization, Ornith collection and public model cards are accessible.
English UIConfirmedThe Hugging Face org page and model cards are English-facing.
API and docsConfirmedModel cards document vLLM, SGLang and Transformers usage plus OpenAI-compatible serving.
International paymentConfirmedWeights are free to download; users pay for their own inference hardware or endpoint hosting.
Commercial usePartialModel cards and Hugging Face metadata list MIT, but production use should verify each variant's LICENSE file and upstream base-model terms.
Data and privacy termsPartialSelf-hosting controls prompts and repository data, but coding-agent deployments still need repository-access, logging and tool-permission controls.

Model names, quotas, release status, regional access and commercial terms can change quickly; recheck official sources before procurement or production use.

Pros

  • - MIT-licensed open weights with 9B, 35B and 397B public checkpoints
  • - GGUF and FP8 variants make local and compressed deployment paths visible
  • - Model cards document vLLM, SGLang and Transformers usage
  • - Benchmarks cover Terminal-Bench 2.1, SWE-Bench, SWE Atlas, NL2Repo and ClawEval

Cons

  • - It is a model family, not a complete coding-agent product with hosted billing or IDE UX
  • - Large variants require substantial multi-GPU infrastructure; 35B and 397B examples use tensor parallel serving
  • - Benchmark claims are vendor/model-card reported and should be reproduced before procurement decisions

Decision paths

qwen-agentworld

qwen-code

kimi-k2-7-code

minimax-m3

zhipu-glm

Sources

DeepReinforce Hugging Face organization

official · en · verified 2026-08-04

Confirms the DeepReinforce org, website, Ornith-1.0 collection, seven public model repositories, datasets and organization card positioning.

Ornith-1.0-397B model card

official · en · verified 2026-06-26

Confirms the 397B MoE model card, MIT license, agentic-coding positioning, benchmark disclosures and vLLM/SGLang serving recipes.

Ornith-1.0-35B model card

official · en · verified 2026-06-26

Confirms the 35B variant, benchmark table, reasoning model behavior and deployment requirements.

Ornith-1.0-9B model card

official · en · verified 2026-06-26

Confirms the 9B dense variant and single-GPU-oriented local serving guidance.

Ornith release blog

docs · en · verified 2026-06-26

Linked from the official model cards as the Ornith blog path.

Last checked: 2026-08-04

Reviews

Availability snapshot

Availability
available
English UI
full
API
available
Rating
4.2 (0)

Latest updates

Latest changes
Release · 2026-06-30

OpenRouter Owl Alpha added

OpenRouter's Owl Alpha is now tracked as a free text model for agentic coding, tool use, automated workflows and complex instruction execution. The live model API lists a 1,048,756-token context window, up to 262,144 output tokens, native tools and structured outputs, zero input and output token prices, and one Stealth INT8 provider route. OpenRouter says it works with Claude Code and OpenClaw, but also warns that the provider may log prompts and completions and use them for model improvement. The underlying model identity and license remain undisclosed, so the profile treats it as a non-sensitive Alpha evaluation route rather than a production-safe default.

Open source · 2026-06-26

DeepReinforce Ornith 1.0 open coding models added

DeepReinforce's Hugging Face organization now exposes the Ornith 1.0 family of MIT-licensed agentic-coding models. The collection includes public 9B, 35B and 397B model cards plus GGUF and FP8 variants. The cards position Ornith as a self-improving model family post-trained from Gemma 4 and Qwen 3.5, using reinforcement learning to optimize both solution rollouts and their scaffolds, with reported results on Terminal-Bench 2.1, SWE-Bench, NL2Repo, SWE Atlas and ClawEval. The profile records vLLM, SGLang, Transformers and OpenAI-compatible local serving paths.

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