Step-2 / Step series is a Flagship from StepFun (China).
One-line fit: best used for Multimodal agents.
Key specifications
| Provider | StepFun |
|---|---|
| Model | Step-2 / Step series |
| Type | Flagship |
| Context window | Very large context claims |
| Pricing (indicative) | API/app |
| Company category | Frontier Lab |
| Region | China |
| Official site | https://www.stepfun.com |
Benchmarks and public standing
CN arena competitive
Treat scores as directional. SWE-bench, Terminal-Bench, LMSYS Arena, Artificial Analysis, and vendor cards use different harnesses and are not always comparable 1:1. Re-check the latest official model card before decisions.
What this model is good at
Multimodal agents
This aligns with StepFun’s broader strengths:
- Multimodal reasoning
- Long context
- Research velocity
Limitations and watch-outs
Less English marketing footprint
- Rate limits, regional availability, and data retention policies vary by plan.
- Agent harness quality (Cursor, Claude Code, Codex, custom tools) can change outcomes more than raw model Elo.
- Open-weight availability (if any) is separate from hosted API quality and safety filters.
Ideal users
- Product engineers shipping features that match: Multimodal agents
- Teams standardizing on the StepFun ecosystem
- Agent builders who need a Flagship
When to pick something else
- Cheaper volume: compare lower tiers from the same lab or open Chinese/EU alternatives.
- Maximum hard SWE thoughtfulness: compare Claude Fable-class and other coding flagships.
- Giant multimodal corpora / Workspace: compare Gemini-class models.
- Self-host / open weights: Llama, Qwen, DeepSeek, GLM, Mistral open lines.
Parent company
StepFun – Step models with strong multimodal and long-context reputation in CN community.
Related models from StepFun
Data is curated for AIForumSphere model directory mid-2026 directional figures.
