Gemini 4 Carbon led the Intelligence Index v5 at launch. Claude Fable 5.2 leads it now

What changed in version 5

Artificial Analysis published version 5 of its Intelligence Index on October 27, 2026, “our biggest upgrade since v4 launched in January.” The index is its single score for how capable a model is, and it now averages nine tests in four equal parts:

Part	Tests, with their weight in the index
Knowledge work, 25%	AA-Briefcase 15%, AutomationBench-AA 5%, GDP.pdf 5%
Coding, 25%	FrontierCode 2.0 15%, Terminal-Bench 4.0 10%
Science, 25%	Terminal-Bench-Science 15%, CritPt v2 hard subset 10%
General, 25%	AA-Omniscience v1.1 15%, HLE-Diamond 10%

Two tests are new. FrontierCode 2.0 is Cognition’s private set of 132 coding tasks in real open-source repositories, “graded on whether a repository maintainer would merge the agent’s change.” Terminal-Bench-Science is 70 scientific research tasks worked in a terminal. HLE-Diamond, a 1,000-question version of Humanity’s Last Exam, replaces the original, and AA-Omniscience and CritPt were revised. GDPval-AA, SciCode and AA-LCR are gone.

Most of it is now private. In Artificial Analysis’s words, “60% of the Index is now based on evaluations with private test sets or held-out answers,” and FrontierCode’s tasks “stay private to avoid contamination,” so models can’t have trained on them. The tests also take more work: the median model wrote 59,000 output tokens per task, up from 35,000 in version 4.3.

Scores from version 4 don’t carry over. Kimi K3.1 Pro scored 55 on version 4.3 and scores 46 now, while Claude Opus 5.5 is at 58 on both.

Who leads

The ten highest-scoring models on October 28, at the effort Artificial Analysis charts for each, with the cost of one index task at API prices:

Model	Score	Cost per task	Where you can use it
Gemini 4 Carbon (high)	59	$7.76	On October 28, cyber defenders in Google’s Fairwind Program; since November 10, Google AI Ultra and the paid Gemini API
Claude Opus 5.5 (max)	58	$10.04	Claude Pro ($20 a month) and Max
GPT-6 Astra (max)	57	$6.24	ChatGPT Plus ($20 a month) and Pro
GPT-6.1 Sol (max)	55	$1.27	ChatGPT Plus and Pro, in Work and Codex
Claude Sonnet 5.5 (max)	54	$10.02	Every Claude plan, Free included
GPT-6.1 Terra (max)	51	$0.96	ChatGPT Plus and Pro, in Work and Codex
Gemini 4 Argon (high)	50	$7.68	Google AI Pro ($19.99 a month) and Ultra
Muse Wonder Full (max)	50	Not given	Muse Code Power ($50 a month) and Maximum
Claude Fable 5.1 (max)	49	$13.04	Claude Max, or Pro with usage credits
Kimi K3.1 Pro	46	$3.68	Kimi’s apps, Kimi Code, the Kimi API, or your own GPUs

The scores and costs are from Artificial Analysis’s leaderboard. It has since moved to version 5.0.1: on November 4, Carbon (high) scored 60, Opus 5.5 (max) 59 and Sonnet 5.5 (max) 55, and a Fable 5.1 (max) task cost $12.99, while the other scores in this table hadn’t changed. The plans are from Claude’s pricing, ChatGPT’s pricing, Codex pricing, Google’s AI plans, Meta’s Muse Code page, Moonshot’s announcement and Google’s announcement of Carbon. Artificial Analysis marks Muse Wonder Full as having no public API, and gives no cost for it.

Artificial Analysis now prices both Gemini 4 models at $4 per million input tokens and $20 per million output, which is what Argon costs on the API from December 1, 2026. Until November 30 it’s $2 and $10, by the Gemini API’s pricing page, so a task at today’s price costs less than the table shows. When this memo was first published, Artificial Analysis charted Argon at its launch price, $3.84 a task.

Gemini 4 Carbon took first place on October 28, a day after the index launched, when only a subset of cyber defenders could use it. On November 10, Google opened it to Google AI Ultra subscribers and the Gemini API’s paid tier (our memo on Carbon). By then it was second: Claude Fable 5.2, which Anthropic released on November 9, scored 65 at max effort, ahead of Carbon’s 60 (our memo on Fable 5.2). Anthropic and OpenAI hold the next five places, and Gemini 4 Argon follows. Further down, Muse Wonder scores 43 at max effort, Claude Haiku 5.5 36, Grok 4.7 35 at high effort, and Gemini 3.8 Flash, the one model Antigravity’s free plan keeps after November 2, 31.

No model leads every test. Gemini 4 Carbon leads HLE-Diamond (69%), Terminal-Bench-Science (65%), AutomationBench-AA, which automates business apps through their APIs (78%, a fraction ahead of Argon), and AA-Omniscience. Opus 5.5 leads FrontierCode 2.0 (46%), and GPT-6 Astra the CritPt physics problems (72%). Claude Sonnet 5.5 leads AA-Briefcase, a test of office work with files; Kimi K3.1 Pro leads Terminal-Bench 4.0 (67%); and Muse Wonder Full leads GDP.pdf, questions answered from long PDFs.

What a task costs, and why effort matters

Cost per task comes from each model’s “input, cache hit, cache write, reasoning, and answer token prices,” so it’s what you’d pay per token on the API. Among the leaders, Artificial Analysis notes that GPT-6.1 Sol “scores within 4 points of Claude Opus 5.5 (max) at about an eighth of the cost per task.” OpenAI charges $2 per million input tokens and $10 per million output for Sol; Anthropic charges $4 and $20 for Opus 5.5. Of the top ten, GPT-6.1 Terra is the cheapest per task and Claude Fable 5.1 the most expensive, more than 13 times as much.

The effort setting, how long a model may think, moves the scores more than it did in version 4.3. Here are the three leaders at each level:

Effort	Claude Opus 5.5	GPT-6 Astra	GPT-6.1 Sol
Low	35, $0.98	43, $1.42	35, $0.16
Medium	48, $2.45	51, $2.73	46, $0.36
High	52, $3.46	55, $3.24	50, $0.59
Extra high	57, $6.05	55, $3.66	52, $0.76
Max	58, $10.04	57, $6.24	55, $1.27

Two things stand out. Opus 5.5 at extra high scores 57 for 60% of max’s cost. And defaults matter: Claude Code starts Opus 5.5 at medium, where it scores 48, three points below GPT-6 Astra at medium.

On a plan there’s no bill per task, but there are limits. Anthropic says how much you can do depends on “the model you choose,” and OpenAI’s Codex pricing that “model choice, context, reasoning, tool use, retrieval, and caching all affect usage.” On ChatGPT Plus, Codex allows 15 to 160 local messages every five hours with GPT-6.1 Sol, against 5 to 45 with GPT-6 Astra.

Open models fall further behind

The best open-weights model, Kimi K3.1 Pro, was 13 points behind the leader, Gemini 4 Carbon, and 12 behind Opus 5.5 on October 28; in version 4.3 the gap was 3. Moonshot published its weights on November 4, and running them takes eight data-center GPUs.

Behind it, DeepSeek V4.1 Flash 1017 and GLM-5.3 scored 32 on October 28. Artificial Analysis put them “26 points behind the leader,” Opus 5.5 at the time, “and below Claude Haiku 5.5 (max, 36).” Science is where they fall furthest: “most open weights models we benchmarked score under 10%” on Terminal-Bench-Science. Of the smaller models people run on their own computers, Qwen3.8 27B scores 20 at extra high effort. Recursive’s Flint isn’t on the leaderboard.

What the scores don’t tell you

• Fallback. The Claude models were scored “with fallback.” When Anthropic’s safety classifiers decline a request, its API can send it on to “the fallback model Anthropic recommends,” so some answers may come from another Claude model. Artificial Analysis’s announcement doesn’t say how often that happened.
• Your agent. The index tests models in setups of Artificial Analysis’s choosing, such as its own harness, Stirrup, not in the agents people use. In Claude Code, Codex or Antigravity, the same model can score differently; the Coding Agent Index measures those pairings.
• Images, speech and other languages. The methodology calls the index “a primarily text-based, English-language evaluation suite.”
• How far a plan goes. The index prices a task; it doesn’t say how many tasks a week a plan allows.

How to choose

1. For the hardest work, Claude Opus 5.5. It led the models you could use on October 28, and FrontierCode, and comes with Claude Pro and Max. Try extra high before max. Claude Fable 5.2 has scored higher since November 9, and comes with Max and Ultra.
2. For the most per dollar, GPT-6.1 Sol. It’s within four points of Opus 5.5 at an eighth of the API cost, and on ChatGPT Plus it allows about three times as many Codex messages as Astra.
3. For science and research, GPT-6 Astra. It leads both science tests.
4. On a Google plan, Gemini 4 Argon, or Carbon on Ultra. Argon scores 50, a fraction behind Carbon on AutomationBench, and comes with Google AI Pro and Ultra. Since November 10, Carbon comes with Ultra only.
5. For open weights, Kimi K3.1 Pro. Its weights came out on November 4, but they need data-center GPUs, so most people will use it hosted.

Using more than one

The leaders split the nine tests between them, and their costs differ by more than ten times, which argues for keeping more than one at hand. Enjoy runs Claude Code, Codex, Antigravity, Muse Code, Grok Build and OpenCode side by side on your computer, each signed in with the account you already have. You can switch agents in the middle of a conversation, and the new agent gets the conversation so far, and you can set the effort in your message, such as “quick one, low effort.”

Enjoy is a monthly subscription, with the first seven days free (pricing). It doesn’t add Opus to a ChatGPT plan or GPT to a Claude one: each agent works on its own lab’s plan.

We’ll update this memo when Artificial Analysis changes the index again.