prime-rl

Headlines · 3

1. Oct 23
   Prime Intellect extends Mega MoE for distributed training

   Prime Intellect says it extended DeepSeek's forward-only Mega MoE kernel with an overlapping backward pass, making the fused MoE implementation usable for distributed training. The vendor reports that its Prime Mega MoE kernels run up to 3.11 times faster than the default PyTorch implementation, while end-to-end training reaches 1.34 times the Prime-RL baseline throughput. Benchmarks used H200 GPUs with Qwen3-30B-A3B and Qwen3-235B-A22B in FP8 configurations.

   Prime Intellect Blog · 🔥 0
2. Oct 19
   prime-rl 0.10.0 releases with IPO default and unified evals

   Prime Intellect released prime-rl 0.10.0 and verifiers 0.4.0, making the new INTELLECT Policy Optimization (IPO) loss the default for asynchronous reinforcement learning. The release adds optimized model support, including DeepSeek V4 Flash, Qwen3.8 Flash Next and Nemotron-H, and consolidates evaluation into prime-rl. Prime Intellect reports that prime-rl was 1.15 times faster than torchtitan in its Qwen3-235B-A22B supervised fine-tuning comparison, though the benchmark details come from the vendor.

   Prime Intellect Blog · 🔥 0
3. Oct 15
   Prime Intellect and Nvidia post-train Nemotron 3.5 Super VL for enterprise agents

   Prime Intellect and NVIDIA built 2,500 verified training tasks aimed at teaching long-horizon enterprise agent work. According to the Prime Intellect blog, 100 GRPO steps — about 11 hours of training on 128 NVIDIA GB200 GPUs — took NVIDIA Nemotron 3.5 Super VL from 34.0% to 57.7% on AutomationBench-AA (public split), a 23.7-point gain over its starting SFT checkpoint. Each task is scored on actual changes to simulated business applications and files, with objectives the agent must complete and guardrails it must not break. The environment library, trainer and templating used for validation are open source, and the same loop runs as a hosted service on Prime Intellect Lab.

   Prime Intellect Blog · 🔥 0

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