StepFun Step 3.5 Flash vs T-AI-LOR

Which one should you pick? Here's the full breakdown.

Our Pick

StepFun Step 3.5 Flash

B
7.8/10

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

T-AI-LOR

B
7.5/10

AI resume tailoring that matches your real experience to any job description in 30 seconds

CategoryStepFun Step 3.5 FlashT-AI-LOR
Ease of Use6.09.0
Output Quality8.07.0
Value9.08.0
Features8.06.0
Overall7.87.5

Pricing Comparison

FeatureStepFun Step 3.5 FlashT-AI-LOR
Free TierYesYes
Starting Price$0$0

Which Should You Pick?

Pick StepFun Step 3.5 Flash if...

  • Higher output quality (8 vs 7)
  • Better value for money (9/10)
  • More features (8 vs 6)

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 Flash

Pick T-AI-LOR if...

  • Easier to use (9 vs 6)

Active job seekers who apply to multiple positions and need to quickly tailor their resume for each application. Especially useful for getting past ATS filters.

Visit T-AI-LOR

Our Verdict

StepFun Step 3.5 Flash and T-AI-LOR 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 T-AI-LOR works best for active job seekers who apply to multiple positions and need to quickly tailor their resume for each application.