Nemotron (Nvidia) vs StepFun Step 3.5 Flash
Which one should you pick? Here's the full breakdown.
Nemotron (Nvidia)
Nvidia's open-weights family -- hybrid Mamba-Transformer MoE architecture, optimized for efficient reasoning on Nvidia hardware
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 | Nemotron (Nvidia) | StepFun Step 3.5 Flash |
|---|---|---|
| Ease of Use | 6.5 | 6.0 |
| Output Quality | 8.0 | 8.0 |
| Value | 8.0 | 9.0 |
| Features | 8.5 | 8.0 |
| Overall | 7.8 | 7.8 |
Pricing Comparison
| Feature | Nemotron (Nvidia) | StepFun Step 3.5 Flash |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0 |
Benchmark Head-to-Head
Nemotron 3 Ultra (253B) benchmarks — StepFun Step 3.5 Flash has no published benchmarks
| Benchmark | Description | Score |
|---|---|---|
| MMLU-Pro | Harder multi-subject reasoning | 79.8% |
| GPQA Diamond | Graduate-level science questions | 70.5% |
| AIME 2025 | 84.5% | |
| HumanEval | Python code generation | 89.6% |
| MMLU (Llama-Nemotron 70B) | 88.4% |
Which Should You Pick?
Pick Nemotron (Nvidia) if...
Teams running on Nvidia hardware (TensorRT-LLM, NIM) who need efficient long-context reasoning. Nemotron 3 Super is a standout for its 8 GB VRAM footprint with strong reasoning.
Visit Nemotron (Nvidia)Pick StepFun Step 3.5 Flash if...
- ✓Better value for money (9/10)
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
Nemotron (Nvidia) and StepFun Step 3.5 Flash are extremely close overall. Your choice comes down to specific needs -- Nemotron (Nvidia) is better for teams running on nvidia hardware (tensorrt-llm, nim) who need efficient long-context reasoning, 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.