Google's fourth-generation open dense model with native multimodal understanding.
NVIDIA's open multimodal mixture-of-experts model, with 12B active parameters out of 120B total.
No shared demos for these models yet.
No captured outputs for these models yet.
Both Gemma 4 31B and Nemotron 3.5 Super VL are capable AI models. The best choice depends on your specific use case: consider pricing, context window, speed, and which capabilities (vision, reasoning, audio) you need.
Nemotron 3.5 Super VL has a lower blended cost. Gemma 4 31B: $0.20 input / $0.40 output. Nemotron 3.5 Super VL: $0.10 input / $0.40 output.
Gemma 4 31B has a larger context window: Gemma 4 31B supports 262K tokens vs Nemotron 3.5 Super VL at 262K tokens.
Yes, both Gemma 4 31B and Nemotron 3.5 Super VL support vision/image input.
Gemma 4 31B and Nemotron 3.5 Super VL have similar overall capabilities. The main differences lie in pricing, context window size, and provider-specific strengths. Use this comparison page to review all metrics side by side.
If cost is your priority, choose the cheaper option. If you need the highest intelligence for complex tasks, pick the higher-scoring model. For long documents or codebases, choose the larger context window. You can try both Gemma 4 31B and Nemotron 3.5 Super VL for free on idapt.app to see which performs better for your specific needs.