Gemini 4 Carbon Stumbles On Agentic Latency

Carbon looks optimized for maximum answer quality, but its latency makes it a poor default for fast feedback loops.

• –Startup delays compound across multi-step coding agents and tool calls
• –Higher reasoning effort can improve difficult tasks while dramatically increasing token usage and cost
• –Google’s benchmarks show strong agentic coding performance, but real-world responsiveness remains a separate metric
• –Developers may get better results by routing routine edits to faster models and reserving Carbon for complex debugging or planning
• –The criticism highlights a broader gap between benchmark leadership and usable production latency