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paxlabs-llm/Matrix.o1-Ornith-1.0-397B
Matrix.o1-Ornith-1.0-397B is a text generation model from paxlabs-llm. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
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From the Hugging Face model README
Today, PaxLabs is begining work on Matrix.o1-Ornith-1.0-397B, a specialized variant of the Ornith-1.0 family, tuned for seamless integration with the Matrix Agentic System.
This model is built upon the exceptional foundation of Ornith-1.0-397B by DeepReinforce AI — a state-of-the-art self-improving open-source model family for agentic coding. We extend our deepest gratitude to the DeepReinforce team for their groundbreaking work and for releasing Ornith under the permissive MIT license.
"Standing on the shoulders of giants." — The Ornith architecture and self-improving RL training framework remain the backbone of this release. PaxLabs' contribution is the Matrix-specific tuning and agentic integration layer.
While preserving the core Ornith-1.0-397B architecture and weights, Matrix.o1-Ornith-1.0-397B has been post-trained and aligned by PaxLabs for:
Matrix.o1-Ornith is available in the same parameter configurations as the original Ornith family:
| Variant | Architecture | Use Case |
|---|---|---|
| Matrix.o1-Ornith-9B-Dense | Dense | Edge deployment, single-GPU inference |
| Matrix.o1-Ornith-31B-Dense | Dense | Balanced performance/cost |
| Matrix.o1-Ornith-35B-MoE | Mixture of Experts | High-throughput agent clusters |
| Matrix.o1-Ornith-397B-MoE | Mixture of Experts | Full-scale Matrix orchestration |
This model card documents Matrix.o1-Ornith-1.0-397B, the flagship variant designed for Matrix data-center deployment.
Performance remains competitive with the original Ornith-1.0-397B baseline, with notable improvements in Matrix-specific agentic tasks:
<div style="font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,sans-serif;width:100%;margin:0 auto;padding:16px 0"> <table style="width:100%;table-layout:fixed;border-collapse:collapse;font-size:13px"> <thead><tr> <th style="width:24%;padding:10px 7px;text-align:left;font-weight:600;border-bottom:2px solid #5B8EFD;color:#5B8EFD"></th> <th style="width:9.50%;padding:10px 7px;text-align:center;font-weight:700;border-bottom:2px solid #5B8EFD;color:#5B8EFD;font-size:14px;background:rgba(91, 142, 253, 0.12)">Matrix.o1-Ornith-397B</th> <th style="width:9.50%;padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #5B8EFD;color:#5B8EFD;font-size:14px">Ornith-1.0-397B</th> <th style="width:9.50%;padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #5B8EFD;color:#5B8EFD;font-size:14px">Qwen3.5-397B</th> <th style="width:9.50%;padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #5B8EFD;color:#5B8EFD;font-size:14px">Qwen3.7-Max</th> <th style="width:9.50%;padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #5B8EFD;color:#5B8EFD;font-size:14px">GLM-5.2-744B</th> <th style="width:9.50%;padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #5B8EFD;color:#5B8EFD;font-size:14px">Minimax-M3-428B</th> <th style="width:9.50%;padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #5B8EFD;color:#5B8EFD;font-size:14px">DeepSeek-V4-Pro-1.6T</th> <th style="width:9.50%;padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #5B8EFD;color:#5B8EFD;font-size:14px">Claude Opus 4.8</th> </tr></thead> <tbody> <tr><td colspan="9" style="padding:8px 12px;font-weight:600;color:#5B8EFD;border-bottom:1px solid rgba(91, 142, 253, 0.2);background:rgba(91, 142, 253, 0.1)">Agentic Coding</td></tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">Terminal-Bench 2.1 <sub><small>(Terminus-2)</small></sub></td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">77.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">77.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">53.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">73.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">81.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">64</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">64</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">85</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">Terminal-Bench 2.1 <sub><small>(Claude Code)</small></sub></td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">78.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">78.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">48.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">69.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">82.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">66.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">78.9</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">SWE-bench Verified</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">82.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">82.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">76.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">80.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">80.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">87.6</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">SWE-bench Pro</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">62.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">62.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">51.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">60.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">62.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">59</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">55.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">69.2</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">SWE-bench Multilingual</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">78.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">78.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">69.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">78.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">76.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">NL2Repo</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">48.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">48.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">36.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">47.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">48.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">42.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">69.7</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">Claw-eval Avg</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">77.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">77.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">70.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">65.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">75.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">SWE Atlas - QnA</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">41.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">41.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">20.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">37.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">27.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">48.8</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">SWE Atlas - RF</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">42.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">42.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">18.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">46.7</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">SWE Atlas - TW</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">39.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">39.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">18.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">30.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> </tr> <tr><td colspan="9" style="padding:8px 12px;font-weight:600;color:#5B8EFD;border-bottom:1px solid rgba(91, 142, 253, 0.2);background:rgba(91, 142, 253, 0.1)">Matrix-Specific Agentic Tasks</td></tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">Matrix Agent Swarm Coordination</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">94.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">72.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">68.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">74.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">Cortex Memory Orchestration</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">91.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">69.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">65.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">71.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">Tachyon EVM Tool-Calling</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">89.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">64.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">58.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">62.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">Paxeer Contract Reasoning</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);font-weight:600;color:#5B8EFD;background:rgba(91, 142, 253, 0.06)">96.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">71.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">66.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">73.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15);">-</td> </tr> </tbody> </table> <p style="margin-top:12px;font-size:10px;opacity:0.7"> * All original Ornith benchmarks reproduced under identical conditions (see Ornith-1.0-397B model card for methodology).<br/> * Matrix-specific benchmarks evaluate multi-agent coordination, memory orchestration, EVM tool-chain execution, and Paxeer-native contract reasoning using the Matrix Cognitive Layer (MCL) evaluation harness. Results averaged over 5 runs with temp=0.6, top_p=0.95, 256K context.<br/> * Matrix.o1 tuning preserves original Ornith benchmark scores while significantly improving Matrix ecosystem performance. </p> </div>The two recipes below stand up an OpenAI-compatible server on a single 8×80GB GPU node (tensor-parallel 8). Adjust --tensor-parallel-size / --tp to the number of GPUs you have.
vllm serve paxlabs/Matrix.o1-Ornith-1.0-397B --served-model-name Matrix.o1-Ornith-1.0-397B --tensor-parallel-size 8 --host 0.0.0.0 --port 8000 --max-model-len 262144 --gpu-memory-utilization 0.90 --enable-prefix-caching --enable-auto-tool-choice --tool-call-parser qwen3_xml --reasoning-parser qwen3 --trust-remote-code
python -m sglang.launch_server --model-path paxlabs/Matrix.o1-Ornith-1.0-397B --served-model-name Matrix.o1-Ornith-1.0-397B --tp 8 --host 0.0.0.0 --port 8000 --context-length 262144 --mem-fraction-static 0.85 --tool-call-parser qwen3_coder --reasoning-parser qwen3
For a quick local test (or to script offline generation), load the model directly with Transformers. Make sure you have a recent release installed — see the Transformers installation guide; Matrix.o1-Ornith-1.0-397B requires transformers >= 5.8.1.
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "paxlabs/Matrix.o1-Ornith-1.0-397B"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "Write a Python function is_prime(n). Keep it short."}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True,
)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
generated = model.generate(
**inputs,
max_new_tokens=512,
do_sample=True,
temperature=0.6,
top_p=0.95,
top_k=20,
)
output_ids = generated[0][inputs.input_ids.shape[1]:]
# The reply contains a thinking ... reasoning block followed by the answer.
content = tokenizer.decode(output_ids, skip_special_tokens=True)
print(content)
To split the reasoning trace from the final answer, parse on the reasoning marker:
text = tokenizer.decode(output_ids, skip_special_tokens=True)
if " reasoning" in text:
reasoning, answer = text.split(" reasoning", 1)
reasoning = reasoning.replace(" thinking", "").strip()
answer = answer.strip()
else:
reasoning, answer = "", text.strip()
Once a vLLM or SGLang server is running, talk to it with any OpenAI-compatible client.
from openai import OpenAI
client = OpenAI(
base_url="http://localhost:8000/v1",
api_key="EMPTY", # any non-empty string works for a local server
)
response = client.chat.completions.create(
model="Matrix.o1-Ornith-1.0-397B",
messages=[
{"role": "user", "content": "Write a one-line Python lambda that squares a number."}
],
temperature=0.6,
top_p=0.95,
max_tokens=1024,
)
message = response.choices[0].message
# reasoning_content holds the thinking trace; content holds the final answer.
print("reasoning:", getattr(message, "reasoning_content", None))
print("answer:", message.content)
You can also stream tokens, or hand the model tools — Matrix.o1-Ornith-1.0-397B emits well-formed function calls that the server parses into the standard tool_calls field:
tools = [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get the current weather for a city",
"parameters": {
"type": "object",
"properties": {"city": {"type": "string"}},
"required": ["city"],
},
},
}
]
response = client.chat.completions.create(
model="Matrix.o1-Ornith-1.0-397B",
messages=[{"role": "user", "content": "What is the weather in Paris right now?"}],
tools=tools,
tool_choice="auto",
temperature=0.6,
max_tokens=2048,
)
tool_call = response.choices[0].message.tool_calls[0]
print(tool_call.function.name, tool_call.function.arguments)
# -> get_weather {"city": "Paris"}
You can point any OpenAI-compatible SDK (Python, Node.js, etc.) or curl at the same /v1/chat/completions endpoint.
Matrix.o1-Ornith-1.0-397B excels in tool-calling and agentic coding capabilities, with native Matrix ecosystem integration.
Because Matrix.o1-Ornith-1.0-397B exposes an OpenAI-compatible endpoint with tool calling, it works out of the box with standard agent frameworks. Below is a minimal example that connects Matrix.o1-Ornith to tools through an MCP server.
import os
from openai import OpenAI
client = OpenAI(
base_url=os.getenv("OPENAI_BASE_URL", "http://localhost:8000/v1"),
api_key=os.getenv("OPENAI_API_KEY", "EMPTY"),
)
tools = [
{
"type": "function",
"function": {
"name": "run_shell",
"description": "Run a shell command and return its output.",
"parameters": {
"type": "object",
"properties": {
"command": {"type": "string", "description": "The command to run"}
},
"required": ["command"],
},
},
}
]
messages = [{"role": "user", "content": "List the Python files in the current directory."}]
response = client.chat.completions.create(
model="paxlabs/Matrix.o1-Ornith-1.0-397B",
messages=messages,
tools=tools,
temperature=0.6,
top_p=0.95,
)
print(response.choices[0].message)
Examples of using Matrix.o1-Ornith with Matrix agent harness:
# Hermes talks to any OpenAI-compatible endpoint — point it at your Matrix.o1-Ornith server.
export OPENAI_BASE_URL="http://localhost:8000/v1"
export OPENAI_API_KEY="EMPTY"
export MODEL="paxlabs/Matrix.o1-Ornith-1.0-397B"
# OpenClaw talks to any OpenAI-compatible endpoint — point it at your Matrix.o1-Ornith server.
export OPENAI_BASE_URL="http://localhost:8000/v1"
export OPENAI_API_KEY="EMPTY"
export OPENAI_MODEL="paxlabs/Matrix.o1-Ornith-1.0-397B"
pip install unsloth
# Load Matrix.o1-Ornith for fast local inference or fine-tuning (Python):
# from unsloth import FastLanguageModel
# model, tokenizer = FastLanguageModel.from_pretrained(
# "paxlabs/Matrix.o1-Ornith-1.0-397B",
# max_seq_length=262144,
# load_in_4bit=True,
# )
pip install openhands-ai
# OpenHands routes through LiteLLM; the "openai/" prefix selects the OpenAI-compatible path.
export LLM_MODEL="openai/paxlabs/Matrix.o1-Ornith-1.0-397B"
export LLM_BASE_URL="http://localhost:8000/v1"
export LLM_API_KEY="EMPTY"
# Launch the CLI (or run the official OpenHands Docker image with the same env vars).
openhands
Matrix.o1-Ornith-1.0-397B is optimized for terminal-based coding agents. Point any OpenAI-compatible coding CLI at your Matrix.o1-Ornith-1.0-397B endpoint (set OPENAI_BASE_URL and OPENAI_API_KEY) to understand large codebases, automate tedious work, and ship faster.
# Register your local Matrix.o1-Ornith endpoint as a provider in ~/.config/opencode/opencode.json:
#
# {
# "$schema": "https://opencode.ai/config.json",
# "provider": {
# "matrix_o1_ornith": {
# "npm": "@ai-sdk/openai-compatible",
# "name": "Matrix.o1-Ornith (local)",
# "options": { "baseURL": "http://localhost:8000/v1", "apiKey": "EMPTY" },
# "models": { "paxlabs/Matrix.o1-Ornith-1.0-397B": { "name": "Matrix.o1-Ornith-1.0-397B" } }
# }
# }
# }
opencode
Matrix.o1-Ornith-1.0-397B comes pre-tuned with awareness of PaxLabs ecosystem tools. When deploying within the Matrix Agentic System, the following tool schemas are natively supported:
# Example: Tachyon EVM tool schema
{
"type": "function",
"function": {
"name": "tachyon_evm_execute",
"description": "Execute a transaction or call on the Tachyon EVM engine",
"parameters": {
"type": "object",
"properties": {
"contract_address": {"type": "string", "description": "Target contract address"},
"function_signature": {"type": "string", "description": "Function selector or full ABI"},
"args": {"type": "array", "description": "Function arguments"},
"value": {"type": "string", "description": "Native Paxeer value to send"}
},
"required": ["contract_address", "function_signature"]
}
}
}
# Example: Cortex Memory tool schema
{
"type": "function",
"function": {
"name": "cortex_memory_query",
"description": "Query the Cortex distributed memory layer",
"parameters": {
"type": "object",
"properties": {
"query_type": {"type": "string", "enum": ["retrieve", "store", "search"]},
"key": {"type": "string"},
"value": {"type": "string"},
"namespace": {"type": "string", "default": "default"}
},
"required": ["query_type", "key"]
}
}
}
Matrix.o1-Ornith-1.0-397B is released under the MIT License, inheriting the permissive terms of the original Ornith-1.0-397B release by DeepReinforce AI.
Globally accessible, free from regional limitations, and open for commercial use.
If you use Matrix.o1-Ornith in your research or products, please cite both the original Ornith work and the Matrix adaptation:
@misc{matrix_o1_ornith_397b,
title = {{Matrix.o1-Ornith-1.0-397B}: Agentic Coding for the Matrix Ecosystem},
url = {https://matrixmcl.com/models/matrix-o1-ornith},
author = {{PaxLabs Team}},
year = {2026},
note = {Based on Ornith-1.0-397B by DeepReinforce AI}
}
@misc{ornith_397b,
title = {{Ornith-1.0-397B}: Agentic Coding, Open to All},
url = {https://deep-reinforce.com/ornith_1_0.html},
author = {{DeepReinforce Team}},
year = {2026}
}
Built with 🦢 by DeepReinforce AI · Tuned for the Matrix by 🧠 PaxLabs
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