StepFun Step 3.5 Flash vs LangGraph
Which one should you pick? Here's the full breakdown.
StepFun Step 3.5 Flash
StepFun's (China) agent-focused open-weight model -- Step 3.5 Flash launched 2026-02-01. 196B sparse MoE, ~11B active. Benchmarks slightly ahead of DeepSeek V3.2 at over 3x smaller total size. Step 3 (321B / 38B active, Apache 2.0) and Step3-VL-10B multimodal also in the family
LangGraph
LangChain's graph-based framework for building stateful, controllable multi-agent and human-in-the-loop AI workflows
| Category | StepFun Step 3.5 Flash | LangGraph |
|---|---|---|
| Ease of Use | 6.0 | 6.0 |
| Output Quality | 8.0 | 9.0 |
| Value | 9.0 | 8.5 |
| Features | 8.0 | 9.5 |
| Overall | 7.8 | 8.3 |
Pricing Comparison
| Feature | StepFun Step 3.5 Flash | LangGraph |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0 |
Which Should You Pick?
Pick StepFun Step 3.5 Flash if...
Teams building agent systems on Chinese open-weight foundations who want something other than DeepSeek or Qwen, especially if agentic tool-use is the primary workload. Also good for Chinese-market products where StepFun's domestic tuning advantages matter. And for anyone looking to add diversity to their open-weight evaluation matrix beyond the top-3 Chinese labs.
Visit StepFun Step 3.5 FlashPick LangGraph if...
- ✓Higher output quality (9 vs 8)
- ✓More features (9.5 vs 8)
Developers building complex, stateful, or human-in-the-loop agent workflows where the logic is genuinely a graph -- loops, branches, approvals, retries. Also the right pick for teams already on LangChain who want serious production tracing and evaluation.
Visit LangGraphOur Verdict
LangGraph edges out StepFun Step 3.5 Flash with a 8.3 vs 7.8 overall score. Both are solid picks, but LangGraph has the advantage in output quality.