Step 5 Preview
600B open weights, trained for long-running agents
Step 5 Preview launched on October 16, 2026 with 79 votes, #267 of 3,394 launches that month and more than 95% of that year's launches.
What it does
Step 5 Preview is StepFun's open-weight MoE for coding, financial research and long-running agents. It has 600B total parameters, 27B active per token and a 1M-token context, with deployment support for vLLM, SGLang and Transformers.
阶跃星辰于2023年4月成立,以“智能阶跃,十倍每个人的可能”为使命。阶跃星辰坚定自研超级模型,积极布局算力、数据等关键资源,发挥算法和人才优势,已完成 Step-1 千亿参数语言大模型和 Step-1V 千亿多模态大模型的研发,在图像理解、多轮指令跟随、数学能力、逻辑推理、文本创作等方面性能达到业界领先水平。
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Terminal-Bench-RL: Training long-horizon terminal agents with RL2025 · github.com · ▲125After training calculator agent via RL, I really wanted to go bigger! So I built RL infrastructure for training long-horizon terminal/coding agents that scales from 2x A100s to 32x H100s (~$1M worth of compute!) Without any training, my 32B agent hit #19 on Terminal-Bench leaderboard, beating Stanford's Terminus-Qwen3-235B-A22! With training... well, too expensive, but I bet the results would be good! *What I did*: - Created a Claude Code-inspired agent (system msg + tools) - Built Docker-isolated GRPO training where each rollout gets its own container - Developed a multi-agent…


I RL-trained an agent that trains models with RL (for ~$1.3k)Jul 2026 · github.com · ▲107RL-training an AI agent to RL-train AI agents. Contribute to Danau5tin/ai-trains-ai development by creating an account on GitHub.

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