{
  "id": 19599425,
  "title": "Praxis-1: A Developer's Checklist Before You Run an Open Robot Model on Your Hardware",
  "url": "https://urgent.news/2026/11/12/praxis-1-a-developers-checklist-before-you-run-an-open-robot-model-on",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-11-12T04:37:10.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/shivaysinghrajput/praxis-1-a-developers-checklist-before-you-run-an-open-robot-model-on-your-hardware-2j9"
  },
  "original_language": "en",
  "account": "Before deploying an open robot model like Praxis-1 on real hardware, developers should follow a checklist to ensure safe and effective operation. First, select the appropriate checkpoint checkpoint, either the base mid-trained model, one fine-tuned on DROID, or one fine-tuned for the bimanual YAM robot. The DROID fine-tune is recommended for single-arm tabletop work. Second, accurately size the GPU for the model. The full bf16 weights require a single 80 GB GPU, but the NVFP4 4-bit version is 68% smaller and achieves similar performance. Third, estimate the cost of running the model, which is approximately $0.12 per 10-minute task. Fourth, properly bind the hardware before trusting the model's policy. The open weights do not guarantee plug-and-play motion, so the model's format must be mapped to the hardware's expected format, and local demonstrations may be necessary for fine-tuning. Fifth, design for the model's performance of 46.2%, rather than aiming for 100%. Build a loop to attempt, verify, and retry or re-plan tasks. Sixth, verify the checkpoint like code, as it has the potential to move hardware. Check the publisher, checkpoint hash, and version, diff against a known-good baseline, audit the checkpoint, and simulate before running unsupervised on a real robot. Lastly, test the model on your specific embodiment and tasks, not just the leaderboard results. The key takeaway is that a competitive robot foundation model is now a downloadable asset, and success depends on the quality of demonstrations, a safe loop, and reliable hardware integration.",
  "summary": "Praxis-1: A Developer's Checklist Before You Run an Open Robot Model on Your Hardware Shivam Kumar | November 12, 2026 Runway released Praxis-1 on November 11, 2026 — a 27-billion-parameter world action model with open weights under Apache 2.0, commercial use included. It tops NVIDIA's RoboLab-120 leaderboard at 46.2% success (555 of 1,200 episodes), ahead of FLUX 3 Action at 42.9%, Cosmos3 Nano…",
  "key_points": [
    "Choose appropriate checkpoint: base mid-trained, DROID fine-tuned, or bimanual YAM robot fine-tuned",
    "Size GPU correctly: 80 GB for full bf16 weights, 68% smaller NVFP4 4-bit version",
    "Estimate cost: $0.12 per 10-minute task"
  ],
  "editors_take": "Treating competitive robot foundation models as downloadable assets shifts the developer's burden from training intelligence to managing hardware integration, safety loops, and rigorous checkpoint verification.",
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}