AI21 Jamba2 vs StepFun Step 3.5 Flash
Which one should you pick? Here's the full breakdown.
AI21 Jamba2
AI21 Labs' hybrid SSM-Transformer (Mamba-style) open-weight family -- Jamba2 launched 2026-01-08. Two sizes: 3B dense (runs on phones / laptops) and Jamba2 Mini MoE (12B active / 52B total). Apache 2.0, 256K context, mid-trained on 500B tokens
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
| Category | AI21 Jamba2 | StepFun Step 3.5 Flash |
|---|---|---|
| Ease of Use | 6.5 | 6.0 |
| Output Quality | 8.0 | 8.0 |
| Value | 9.0 | 9.0 |
| Features | 8.5 | 8.0 |
| Overall | 8.0 | 7.8 |
Pricing Comparison
| Feature | AI21 Jamba2 | StepFun Step 3.5 Flash |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0 |
Which Should You Pick?
Pick AI21 Jamba2 if...
Developers building long-context RAG systems (256K context with manageable memory is the sweet spot), mobile/edge deployments where Jamba2 3B's hybrid efficiency shines, and teams that want to experiment with non-transformer architectures while staying in Apache-2.0 territory. Also good for Israeli + EU enterprise procurement where AI21's geography / GDPR posture matters.
Visit AI21 Jamba2Pick 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 FlashOur Verdict
AI21 Jamba2 and StepFun Step 3.5 Flash are extremely close overall. Your choice comes down to specific needs -- AI21 Jamba2 is better for developers building long-context rag systems (256k context with manageable memory is the sweet spot), mobile/edge deployments where jamba2 3b's hybrid efficiency shines, and teams that want to experiment with non-transformer architectures while staying in apache-2, while StepFun Step 3.5 Flash works best 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.