Gemini 4 Carbon is the new #1 on the Artificial Analysis Intelligence Index v5

Your coding assistant now performs with a higher degree of accuracy and reasoning, offering better results for complex tasks at a reduced cost.

Google's Gemini 4 Carbon has achieved the top spot on the Artificial Analysis Intelligence Index v5, scoring 59 and excelling in complex reasoning, knowledge, and scientific tasks. While it shows significant gains in coding and knowledge work compared to previous Gemini models, it is not the leader in all these areas. Gemini 4 Carbon is currently available to select users with a 50% launch discount, and its standard pricing is $7.76 per Intelligence Index task, making it approximately 23% cheaper than Claude Opus 5.5. The model also demonstrates a low hallucination rate, scoring 54 on the updated AA-Omniscience v1.1 benchmark. It ranks second only to Claude Opus 5.5 on the Artificial Analysis Coding Agent Index, a notable improvement for Google in this domain. Gemini 4 Carbon boasts a 1M token context window and supports multimodal inputs including text, image, video, and speech.

The competitive landscape for advanced AI models is intensifying, with Google's Gemini 4 Carbon challenging established leaders like Claude Opus 5.5. While Gemini 4 Carbon leads the overall Intelligence Index, its second-place finish in coding agents, despite significant improvements, suggests that specialized models may still hold an edge in niche applications. The model's substantial gains in agentic knowledge work, though not yet leading, indicate a broader push towards more versatile AI assistants capable of handling complex tasks like presentation generation and analytical quality assessments.

Gemini 4 Carbon's introduction with a significant price discount and a lower cost per task compared to top competitors, alongside its impressive context window and multimodal capabilities, signals a strategic move to capture market share. This pricing strategy, coupled with performance gains, puts pressure on other major cloud providers and AI developers to either match these price points or demonstrate superior value in their offerings. The focus on reduced output tokens and lower hallucination rates also points towards a growing emphasis on efficiency and reliability in AI deployments.