Scale-up possibilities for everyone. API Platform: platform.stepfun.ai/ HuggingFace: huggingface.co/stepfun-ai

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Introducing Step 5 Preview: Advancing the Pareto Frontier. Step 5 Preview is our new flagship model for agentic work, delivering frontier-level performance across software engineering and professional knowledge work, with particular strength in finance. - 600B total / 27B active MoE, with 1M context + Vision - Substantially lower task cost at comparable intelligence - Broad software engineering capabilities with sustained execution over long horizons Try Step 5 Preview: platform.stepfun.ai Model page: stepfun.com/step-5-preview Open weights on Oct 15.
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StepFun retweeted
sf, join us this thursday for step 5 preview launch night with stepfun we’ll dig into the model, building + serving agent workloads, and what’s worth building as models keep improving, with dan fu, hongyu zhou, mar hershenson, saoud rizwan, joey wang rsvp: luma.com/12t5e4lc
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What a weekend at LA Hacks 2026! Beyond connecting with the community at our booth, we hosted a hands-on workshop to help participants get started with Step 5 Preview and explore what they could build with it. We also launched the StepFun Challenge and saw teams made especially thoughtful and effective use of our models. Huge thanks to everyone who stopped by, joined our workshop, or took on the challenge. Congrats to our three winning teams! We loved being part of LA Hacks and can't wait to see what you build next.
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Step 5 Preview weights are out. Now let’s meet in SF.🍷 Join @StepFun_ai and @togethercompute for Step 5 Preview Launch Night & AI Founders Meetup on Thu, Oct 22. On stage: Hongyu Zhou (@StepFun_ai), Dan Fu (@realDanFu · @togethercompute), Mar Hershenson (@MarHershenson · @pearvc), Saoud Rizwan (@sdrzn · @cline), and Joey Wang (@harvey). A first look at Step 5 Preview, live Q&A, and a panel on what's still worth building as AI models get better. Food, drinks & great conversations. A first look at Step 5 Preview, live Q&A, and a panel on what's still worth building as AI models get better. Food, drinks & great conversations. Want to join us? Request your spot here: luma.com/12t5e4lcluma.com/12…
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LA Hacks 2026, here we come! StepFun will be at UCLA on Oct 17–18 to meet builders, exchange ideas, and explore what's possible with Step 5 Preview. We'll also host a workshop on Sat, Oct 17, 8–9 PM PT at James West Alumni Center. Come say hi!
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One week since launch, Step 5 Preview is already #2 on OpenRouter's weekly leaderboard, with 19.5T tokens used. It has also held #2 on the daily leaderboard since Oct 10. Thanks to everyone building with us.
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StepFun retweeted
congrats to the StepFun team on releasing Step 5 Preview open weights today we’re excited to be a launch partner and to support another StepFun release as they bring Step 5 Preview to developers
Step 5 Preview is now open weights. BF16 and FP8 weights are live on Hugging Face and ModelScope, together with our technical blog. • Sparse MoE: 600B total, 27B active per token • 1M-token context window • Native text and vision input • Built for long-horizon agentic work: coding, software engineering, professional knowledge work and finance Frontier intelligence, open weights. Build what's next. Hugging Face: huggingface.co/stepfun-ai/St… ModelScope: modelscope.ai/models/stepfun… GitHub: github.com/stepfun-ai/Step-5…
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A 1M-token context window, endless possibilities. Excited to see Step 5 Preview live on @DeepInfra! Thanks to the team for making it easier for developers to build with Step 5. What will you build first?
Step 5 Preview from @StepFun_ai is live on DeepInfra, day zero. 600B open-weight MoE, 27B active. 1M context, text + vision. FP8. $1.00 in / $2.70 out / $0.05 cached per 1M tokens. Built for long-horizon agents: coding, frontend, finance. What would you load into 1M tokens first?
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Thanks to @radixark for helping power Step 5 Preview in production! Great to see SGLang enabling efficient, scalable inference for real-world workloads. Excited to keep pushing the boundaries together.
Congratulations to @StepFun_ai on Step 5 Preview going open weights! RadixArk is proud to help power StepFun's first-party production API with SGLang at scale. Production inference means great token economics under strict latency requirements. SGLang and its cache-aware routing stack now bring that to Step 5 Preview in proven production traffic. Building with Step 5 Preview? Deploy with SGLang today!
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StepFun retweeted
Congratulations to @StepFun_ai on Step 5 Preview going open weights! RadixArk is proud to help power StepFun's first-party production API with SGLang at scale. Production inference means great token economics under strict latency requirements. SGLang and its cache-aware routing stack now bring that to Step 5 Preview in proven production traffic. Building with Step 5 Preview? Deploy with SGLang today!
Step 5 Preview is now open weights. BF16 and FP8 weights are live on Hugging Face and ModelScope, together with our technical blog. • Sparse MoE: 600B total, 27B active per token • 1M-token context window • Native text and vision input • Built for long-horizon agentic work: coding, software engineering, professional knowledge work and finance Frontier intelligence, open weights. Build what's next. Hugging Face: huggingface.co/stepfun-ai/St… ModelScope: modelscope.ai/models/stepfun… GitHub: github.com/stepfun-ai/Step-5…
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Step 5 Preview: The new pareto frontier of agentic finance is here We ran an experiment: which open model gives the best M&A memo per dollar? We had 6 open models write the same memo for 80 companies, and two other AI judges picked the best
Step 5 Preview is now open weights. BF16 and FP8 weights are live on Hugging Face and ModelScope, together with our technical blog. • Sparse MoE: 600B total, 27B active per token • 1M-token context window • Native text and vision input • Built for long-horizon agentic work: coding, software engineering, professional knowledge work and finance Frontier intelligence, open weights. Build what's next. Hugging Face: huggingface.co/stepfun-ai/St… ModelScope: modelscope.ai/models/stepfun… GitHub: github.com/stepfun-ai/Step-5…
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Great to see Step 5 Preview live on @FeatherlessAI! Frontier-level intelligence, competitive cost efficiency, and easier access for developers.
Step 5 Preview is here. @StepFun_ai's new open-weights model sets a new Pareto frontier, matching Kimi K3 on the @ArtificialAnlys Intelligence Index! It’s built for long-horizon agent work, with frontier-level results on software engineering and professional knowledge work, especially finance. - 600B sparse MoE, 27B active per token - ~1/6 the cost per task of Claude Opus 5.5, per Artificial Analysis Now on Featherless, served at FP8. featherless.ai/model-pages/s…
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Great to see Step 5 Preview delivering strong inference performance on NVIDIA GB300. Looking forward to seeing what developers build with it.
Congrats to StepFun on Step 5 Preview 🙌 Their largest open weights release. The 600B MoE model is built to handle agent tasks lasting up to 24 hours. The model runs at nearly 8K tokens/sec/GPU on NVIDIA GB300 using NVFP4. NVP4 checkpoint: huggingface.co/stepfun-ai/St… Deploy with @SGL_project - docs.sglang.io/cookbook/auto…  or @vLLM_project - recipes.vllm.ai/stepfun-ai/S… Post-train with NeMo Automodel: github.com/NVIDIA-NeMo/Autom… Run it with NVIDIA NIM using a single command: catalog.ngc.nvidia.com/orgs/…
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Step 5 Preview is now open weights. BF16 and FP8 weights are live on Hugging Face and ModelScope, together with our technical blog. • Sparse MoE: 600B total, 27B active per token • 1M-token context window • Native text and vision input • Built for long-horizon agentic work: coding, software engineering, professional knowledge work and finance Frontier intelligence, open weights. Build what's next. Hugging Face: huggingface.co/stepfun-ai/St… ModelScope: modelscope.ai/models/stepfun… GitHub: github.com/stepfun-ai/Step-5…
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Our technical blog, "Inside Step 5 Preview: Architecture and Training for Agentic Work," covers how architecture and training were co-designed for longer, more complex agent tasks: • 92-layer narrow-and-deep architecture for implicit multi-hop reasoning • Sparse GQA to cut million-token context cost, with 8-token block indexing reducing indexing and top-k overhead to 1/8 • FP32 precision on key states plus fine-grained gradient clipping for stable training • Million-scale verifiable environments • RL for long-horizon tasks with context compression built into policy training platform.stepfun.ai/blog/ins…
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We've also updated Step Code to v0.1.4, our open-source agent harness built around Step 5 Preview. It helps agents keep track of the goal on long, complex tasks, keep making progress, and check against verifiable results whether the job is actually done. Four releases since open-sourcing, about one every 3 working days, mostly driven by community feedback. Thank you to everyone who tried it and shared feedback. github.com/stepfun-ai/Step-C…
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Step 5 Preview now exists where you build. Now live on @OpenRouter. A week of free access is rolling out today across @opencode, @cline , @NousResearch, @kilocode, and more. Flagship-tier intelligence for agentic and professional work, at substantially lower task cost. Keep your workflow. Switch your model. Try Step 5 Preview on OpenRouter: openrouter.ai/stepfun/step-5…
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Strong performance, now within reach of more builders through Nous Portal. Step 5 Preview is free to explore for this week.
Step 5 Preview from @StepFun_ai is free on Nous Portal for the next week 600B total / 27B active MoE, 1M context, with vision Step 5 Preview scored 33.89 on Hermes Index, the same score as GPT-6 Luna
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More context. More room to build. Step 5 Preview is now free in @kilocode for one week. See how far you can take it.
Replying to @StepFun_ai
@StepFun_ai just announced Step 5 Preview, and it's FREE in Kilo for a week: • 600B parameters, 27B active per token • 1M-token context + vision • highlights: strong coding and finance performance at lower cost. Try it and let us know what you think!
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Step 5 Preview is now on @OpenRouter's New & Trending leaderboard. Thanks to everyone giving it a try, and to our partners bringing it into your workflow.
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