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Google DeepMind's efficiency-tier multimodal model with a 1M-token context window, optional chain-of-thought thinking, and native support for text, image, audio, video, and file inputs.
Google's fastest Gemini 2.5 variant — a multimodal, 1M-context instruct model built for realtime, high-throughput workloads with optional reasoning mode.
Google's frontier-tier Flash model with a 1M-token context, native multimodal inputs, and opt-in extended thinking — built for fast agentic workflows that need near-Pro reasoning.
Google DeepMind's cost-optimised multimodal language model with a 1M-token context window, real-time latency, and optional extended thinking — built for high-throughput agentic and instruction-following workloads.
Google's frontier reasoning model with a 1M-token context window, dynamic chain-of-thought thinking, and full multimodal input — built for complex, long-horizon inference tasks.
Google DeepMind's frontier-tier multimodal Flash model with a 1M-token context window, optional extended thinking, and native support for text, image, video, audio, and file inputs — built for complex interactive workloads.
Each axis is the mean score across the family’s variants that have been scored on that dimension. Per-axis sample size is shown next to each label — the family currently aggregates up to 5 variants per axis.
Values aggregated across the family’s variants: any variant supporting a capability resolves the family to Supported; flag-driven support resolves to Optional; only when every variant explicitly denies a capability does the family render as Not supported. 15 of 15 capabilities have variant data so far.