StepFun Step 3.5 Flash vs NotebookLM
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
NotebookLM
Google's free research assistant that turns your documents into an AI you can query -- and a podcast you can listen to
| Category | StepFun Step 3.5 Flash | NotebookLM |
|---|---|---|
| Ease of Use | 6.0 | 8.0 |
| Output Quality | 8.0 | 7.0 |
| Value | 9.0 | 9.5 |
| Features | 8.0 | 6.5 |
| Overall | 7.8 | 7.8 |
Pricing Comparison
| Feature | StepFun Step 3.5 Flash | NotebookLM |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0 |
Which Should You Pick?
Pick StepFun Step 3.5 Flash if...
- ✓Higher output quality (8 vs 7)
- ✓More features (8 vs 6.5)
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 NotebookLM if...
- ✓Easier to use (8 vs 6)
Students researching papers, professionals who need to quickly digest long documents, and anyone who wants to turn a pile of PDFs into something they can query and listen to.
Visit NotebookLMOur Verdict
StepFun Step 3.5 Flash and NotebookLM are extremely close overall. Your choice comes down to specific needs -- StepFun Step 3.5 Flash is better for 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, while NotebookLM works best for students researching papers, professionals who need to quickly digest long documents, and anyone who wants to turn a pile of pdfs into something they can query and listen to.