Google's open multimodal model with 128K context and 140+ language support.
Open-source 1.6T-parameter MoE with 49B active, built for advanced reasoning and long-horizon agents.
No shared agent demos for these models yet.
No captured outputs for these models yet.
Based on the Capability Index, DeepSeek V4 Pro scores higher (81.6 vs 64.6). However, "better" depends on your use case — pricing, speed, context window, and specific capability needs all matter.
Gemma 3 27B has a lower blended cost. Gemma 3 27B: $0.10 input / $0.30 output. DeepSeek V4 Pro: $0.43 input / $0.87 output.
DeepSeek V4 Pro has a larger context window: Gemma 3 27B supports 110K tokens vs DeepSeek V4 Pro at 1M tokens.
Gemma 3 27B supports vision/image input, but DeepSeek V4 Pro does not.
Key differences: DeepSeek V4 Pro has a notably higher capability index (17.0 point gap); Gemma 3 27B is significantly cheaper; only Gemma 3 27B supports vision input; only DeepSeek V4 Pro offers extended reasoning mode. Compare full specs on this page.
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 3 27B and DeepSeek V4 Pro for free on idapt.app to see which performs better for your specific needs.