Google Deepmind releases Gemini 4 Carbon just two weeks after Argon with gains across the board

Google Deepmind shipped Gemini 4 Carbon just two weeks after Argon, and the new model takes the top spot on the Artificial Analysis Intelligence Index.

Carbon scores 59 points on the recently updated version 5.0 of the Artificial Analysis Intelligence Index, while predecessor Argon trails at 50. Beyond general gains in agentic tasks and programming, Google highlights capabilities spanning the full cyber defense lifecycle, from detecting and validating vulnerabilities to patching them.

Built for multi-day coding sessions

Google Deepmind says it designed Carbon for "much harder, long-horizon engineering problems" that demand persistent agentic workflows. Internal teams ran the model for multiple days straight, during which it worked through dead ends on its own and handled complex, multi-step tasks like root-cause analysis and subtle bug fixes in large codebases and low-level software, Google claims.

Google also reports improvements in scientific reasoning, multimodal understanding, and full-stack web development based on user feedback. Higher-quality outputs and artifacts in web development pushed Carbon up 89 Elo points on the WebDev Arena, where it sits in fourth place at 1,769.

On Gray Swan's indirect prompt injection benchmark, Carbon pushed the attack success rate from 0.7 percent with Argon down to 0.0 percent, blocking every tested manipulation attempt according to Google. That doesn't mean prompt injection is solved, but the test appears to be saturated.

Independent evaluations back up Google's numbers

According to Artificial Analysis, Carbon at its highest reasoning tier ("high") leads the Intelligence Index v5 mainly because of top scores in complex reasoning, knowledge retrieval, and scientific tasks, taking first place in four of the index's nine individual evaluations.

In agentic coding on Antigravity, Carbon still trails Claude Code with Opus 5.5 by three points, despite jumping from 53 to 59 compared to Argon. In agentic knowledge work on AA-Briefcase, Carbon (high) gains 126 points over Argon (high, 1,483 Elo) to reach 1,609 Elo, driven by presentation quality (+293 Elo to 1,598) and analytical quality (+120 Elo to 1,671). It still falls behind Kimi K3.1 Pro (1,678 Elo), Muse Wonder (max, 1,659 Elo), and Grok 4.7 (xhigh, 1,638 Elo).

Answer accuracy rises from 48 to 58 percent compared to Argon, while the hallucination rate climbs from four to 11 percent. That's higher but still the second-lowest in the ranking. Claude Opus 5.5 (max) and GPT-6 Astra (max) each sit at 50 percent.

The evaluation platform Vals AI puts Carbon in second place at 70.36 percent accuracy, behind Claude Sonnet 5.5 (70.85 percent) and ahead of Claude Opus 5.5 (70.18 percent) and Argon in fourth (69.24 percent), all at lower cost.

On Vals.ai, Carbon also leads both the Finance Index and the Legal Research benchmark. In legal research, Vals AI recorded roughly 45 percent more cited sources, more frequent tool calls, and longer responses than Argon.

But tasks in the Finance and Tax Agent benchmark take more than twice as long as with Argon, and in Legal Research, Carbon averages more than 50 minutes per task. The model generates 2.3 times as many reasoning tokens and 64 percent more output tokens than Argon, though that's still less than half the output token count of Sonnet 5.5 and Opus 5.5.

On Arena.ai, Gemini 4 Carbon (High) takes the Text Arena lead with 1,528 points, edging past Argon (1,520). In the Agent Arena, the model places second across more than 21,900 real sessions, ahead of GPT-6 Astra and Fable-5.1, with a net improvement of 16.2 percent and the highest steerability score (+18.6 percent). Its median task cost of $1.80 is 72 percent below first-place Claude Opus 5.5 (Max).

In the WebDev category of the Code Arena, Carbon reaches 1,768 points (89 ahead of eleventh-place Argon) for fourth overall, just two behind Claude Sonnet 5.5 (xHigh, 1,770). That places it on the Pareto curve across all three disciplines.

Carbon leads security benchmarks without guardrails

For several security tests, Google ran the model without safety guardrails. On SEC-bench Pro, which measures autonomous vulnerability discovery in real-world software, Carbon scores 88.2 percent and leads all tested models. On ExploitGym, which tests whether a system can turn discovered vulnerabilities into working exploits, the model reaches 54.8 percent. Carbon also holds a wide first-place lead in writing fixes on CWE-Bench.

Google also cites internal results that can't be independently verified. On in-house benchmarks, Carbon reportedly produces secure code more than twice as often as Argon, and in tests by Google's Chrome team, it performed more than ten times better at writing security patches than the frontier model of an unnamed competitor.

Security experts get access first

Google is rolling out the model gradually and participating in the U.S. government's pre-release testing process, citing Carbon's advanced security capabilities. Selected cybersecurity experts get access first starting this week. Through Google Deepmind's Fairwind Program, access will expand to more trusted partners after that.

The company plans to open the model to developers, businesses, and consumers through its product interfaces after collecting more feedback and adjusting the safety guardrails.

Gemini 4 Carbon launches at the same introductory price as Argon: $2 per million input tokens and $10 per million output tokens, with cached input tokens getting a 95 percent discount off the regular input price.

Carbon costs $7.76 per task in the Artificial Analysis Intelligence Index, about 23 percent less than Claude Opus 5.5 (max, $10.04) and roughly 1.2 times more than GPT-6 Astra (max, $6.25). It averages 123,000 output tokens per task, 29 percent fewer than the Anthropic model (173,000 tokens), and lands almost exactly at Argon's price point ($7.68).

Artificial Analysis bases its calculations on the regular list price of $4 per million input tokens and $20 per million output tokens (plus $0.20 for cached input tokens), ignoring the current 50 percent introductory discount that runs through the end of 2026.

AI News Without the Hype – Curated by Humans

Subscribe to THE DECODER for ad-free reading, a weekly AI newsletter, our exclusive "AI Radar" frontier report six times a year, full archive access, and access to our comment section.