StepFun Step 3.5 Flash vs Cohere Transcribe
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
Cohere Transcribe
Cohere's first audio model -- launched 2026-03-26 under Apache 2.0, 2B parameters, #1 on Hugging Face Open ASR Leaderboard (5.42 avg WER), 14 enterprise-critical languages. Free API with rate limits; Model Vault for production
| Category | StepFun Step 3.5 Flash | Cohere Transcribe |
|---|---|---|
| Ease of Use | 6.0 | 7.0 |
| Output Quality | 8.0 | 9.0 |
| Value | 9.0 | 9.0 |
| Features | 8.0 | 7.0 |
| Overall | 7.8 | 8.0 |
Pricing Comparison
| Feature | StepFun Step 3.5 Flash | Cohere Transcribe |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0 |
Which Should You Pick?
Pick StepFun Step 3.5 Flash if...
- ✓More features (8 vs 7)
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 Cohere Transcribe if...
- ✓Higher output quality (9 vs 8)
- ✓Easier to use (7 vs 6)
Enterprise teams transcribing English, European, and major APAC languages at scale who want open weights they can self-host, fine-tune, or deploy on-prem. The Apache 2.0 license removes a major procurement blocker compared to proprietary ASR, and the accuracy tier is now best-in-class for open models.
Visit Cohere TranscribeOur Verdict
StepFun Step 3.5 Flash and Cohere Transcribe 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 Cohere Transcribe works best for enterprise teams transcribing english, european, and major apac languages at scale who want open weights they can self-host, fine-tune, or deploy on-prem.