References 687% CONFIDENCEOverall confidence: 87%How well the pin's source and references back up its dates.Weighted average of how firmly 6 references, the source included, support the pin's start and end times; a reference counts half as much for every 180 days older than the newestShow all pins at 75% confidence or better
The first entry is always the pin's source. Overall confidence is a weighted average of how firmly each reference supports the start and end times used above; a reference counts half as much for every 180 days older than the newest.
- [1]90%static.stepfun.com/blog/step-3.5-flashstatic.stepfun.com· Posted Oct 12, 2026· Starts Feb 2, 2026· 24% of score
AIBase's[6] 2 February 2026 report calls it StepFun's[3] "latest open-source foundation model" with code on GitHub and weights on Hugging Face[2], and the GitHub repository's first commit is dated 2 February; OpenRouter listed it from 29 January and the Hugging Face repo was created on 1 February UTC, so the public launch day is 2 February.
- [2]90%stepfun-ai/Step-3.5-Flash · Hugging Facehuggingface.co· Added Oct 12, 2026· 24% of score
The model card: Apache 2.0, 196B total and about 11B active parameters with 288 routed experts plus one shared and top-8 routing, 256K context, 100-300 tok/s typical and about 350 tok/s peak, 74.4% SWE-bench Verified and 51.0% Terminal-Bench 2.0, recommended sampling.[1]
- [3]85%Step 3.5 Flash - StepFun Documentationplatform.stepfun.ai· Added Oct 12, 2026· 24% of score
The API docs: step-3.5-flash at $0.10 per 1 million input tokens, $0.02 cache hit and $0.30 output; a step-3.5-flash-2603 agent-optimized variant with a low-reasoning mode; OpenAI-compatible chat completions with tool calling.[1]
- [4]70%阶跃星辰 Step 3.5 Flash 全面开源 - 爱范儿ifanr.com· Published Mar 6, 2026· 10% of score
ifanr (6 March): StepFun[1][3] fully open-sourced the model in early March, releasing the Base and Midtrain weights and the Steptron training framework alongside it, with Step 3.5 Flash's OpenClaw call volume reaching first place globally.
- [5]90%Step 3.5 Flash: Open Frontier-Level Intelligence with 11B Active Parameters - arXivarxiv.org· Published Feb 11, 2026· 9% of score
The technical report (216 authors, submitted 11 February, revised 23 February): 3:1 sliding-window/full attention, MTP-3, a reinforcement learning framework, and 85.4% IMOAnswerBench, 86.4% LiveCodeBench-v6, 88.2% tau2-Bench, 69.0% BrowseComp (with context management).[1]
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