Google's fourth-generation open dense model with native multimodal understanding.
DeepSeek's cost-efficient V4.1 tier and the first model built on the Causal Encoder-Decoder (CED) architecture: a 552B MoE activating 8B parameters on input and 16B on output.
No shared demos for these models yet.
No captured outputs for these models yet.
Both Gemma 4 31B and DeepSeek V4.1 Flash 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.
Gemma 4 31B has a lower blended cost. Gemma 4 31B: $0.20 input / $0.40 output. DeepSeek V4.1 Flash: $0.15 input / $0.60 output.
DeepSeek V4.1 Flash has a larger context window: Gemma 4 31B supports 262K tokens vs DeepSeek V4.1 Flash at 1M tokens.
Yes, both Gemma 4 31B and DeepSeek V4.1 Flash support vision/image input.
Gemma 4 31B and DeepSeek V4.1 Flash 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 DeepSeek V4.1 Flash for free on idapt.app to see which performs better for your specific needs.