# Intelligence Index v5: Claude Opus 5.5 Leads at 58

> Artificial Analysis rebuilt its Intelligence Index on private tests. Claude Opus 5.5 leads at 58, GPT-6 Astra 57. Scores, costs and what changed.

- Author: Nitish Garg, Founder & CEO, CellCog
- Published: 2026-10-28
- Canonical (HTML): https://cellcog.ai/blog/artificial-analysis-intelligence-index-v5/
- Section: Guides / Choosing a platform
- Publisher: CellCog (https://cellcog.ai), the AI employee platform. Blog index for agents: https://cellcog.ai/blog/llms.txt

## Key points

- Artificial Analysis published Intelligence Index v5 on October 27, 2026. For the first time, 60% of the Index runs on private test sets or held-out answers.
- Claude Opus 5.5 at max effort leads at 58, ahead of GPT-6 Astra at 57 and GPT-6.1 Sol at 55. Gemini 4 Argon is next at 50.
- No model leads all nine tests: Opus 5.5 leads three, GPT-6 Astra two, and Sonnet 5.5, Kimi K3.1 Pro, Gemini 4 Argon and Muse Wonder Full one each.
- The open-weights gap grew from 3 points to 12. Among released weights, DeepSeek V4.1 Flash 1017 and GLM-5.3 lead at 32, below Claude Haiku 5.5 at 36.
- Effort now moves scores more than before: Opus 5.5 scores 35 at low effort and 58 at max, at $0.98 versus $10.04 per task.

## At a glance

- **Who leads Intelligence Index v5?** Claude Opus 5.5 at max effort, with 58. GPT-6 Astra scores 57 and GPT-6.1 Sol 55, so Anthropic and OpenAI hold the top five models.
- **What changed from v4.3?** Two new tests (FrontierCode 2.0, Terminal-Bench-Science), three upgraded ones, three removed, and 60% of the weight now sits on private or held-out tests.
- **Is the top score worth its price?** It depends on the job. GPT-6.1 Sol scores within 4 points of Opus 5.5 at about an eighth of the cost per task: $1.27 against $10.04.

**Artificial Analysis published Intelligence Index v5 on October 27, 2026, and Claude Opus 5.5 at max effort leads it at 58.** GPT-6 Astra (max) follows at 57 and GPT-6.1 Sol (max) at 55, so Anthropic and OpenAI hold the top five models. Gemini 4 Argon (high) is next at 50. The [announcement](https://artificialanalysis.ai/articles/artificial-analysis-intelligence-index-v5) calls v5 the biggest upgrade since v4 launched in January.

The larger change sits under the scores: "With v5, 60% of the Index is now based on evaluations with private test sets or held-out answers." Most of the exam can no longer be studied for, and the ranking it produces looks different from v4.3. The open-weights gap grew from 3 points to 12, and how hard a model is allowed to think now moves its score by more than the gap between the top labs.

## What changed in v5

![Animated scene: four equal blocks, Knowledge Work, Coding, Science and General at 25% each, a padlock marks 60% private tests, then four bars grow: Claude Opus 5.5 58, GPT-6 Astra 57, GPT-6.1 Sol 55, Gemini 4 Argon 50](https://cellcog.ai/blog/media/artificial-analysis-intelligence-index-v5/exam.svg)
*v5 splits into four equal groups, mostly private tests; Opus 5.5 leads at 58.*

Two benchmarks are new: FrontierCode 2.0 and Terminal-Bench-Science, 70 agentic research tasks run in a terminal. Three are upgraded: HLE-Diamond replaces Humanity's Last Exam, AA-Omniscience v1.1 drops saturated and public questions, and CritPt v2 is scored on a private 40-question hard subset. GDPval-AA v2.1, SciCode and AA-LCR v1.1 left the Index.

*Table: How the v5 Index is weighted (October 27, 2026)*

| Group | Weight | Tests inside |
|---|---|---|
| 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% |

FrontierCode 2.0 is [Cognition's new coding benchmark](https://cognition.com/blog/frontier-code-2.0), launched the same morning. Its 132 tasks sit in real open-source repositories and are graded on whether a maintainer would merge the change; an attempt that fails any blocking check scores 0. Cognition built it because, in its words, "Models struggle to infer user intent, respect unstated constraints, and anticipate long-term consequences of their changes, forcing human intervention." Artificial Analysis runs each task three times in its own harness, Stirrup. Opus 5.5 leads at 46%, with GPT-6 Astra, GPT-6.1 Terra and Claude Sonnet 5.5 at 42%. The best open-weights model, DeepSeek V4.1 Flash 1017, scores 28%. We covered the same benchmark's debut in the [Coding Agent Index v2.0](https://cellcog.ai/blog/artificial-analysis-coding-agent-index/).

## The scores

The top open-weights model is Kimi K3.1 Pro at 46, but its weights were not yet released when the Index went up. Among models with released weights, DeepSeek V4.1 Flash 1017 and GLM-5.3 lead at 32, 26 points behind the leader and below Claude Haiku 5.5. The gap is widest on HLE-Diamond, where Kimi K3.1 Pro scores 37% against 68% for Opus 5.5, and on Terminal-Bench-Science, 34% against 63% for GPT-6 Astra.

## No model wins all nine

"v5 leaves significant room for progress across all nine evaluations, and no single model leads them all," Artificial Analysis writes. Opus 5.5 leads three tests, and five other models split the remaining six.

*Table: Who leads each of the nine v5 tests (October 27, 2026)*

| Test | Leader | Score |
|---|---|---|
| FrontierCode 2.0 | Claude Opus 5.5 | 46% |
| HLE-Diamond | Claude Opus 5.5 | 68% |
| AA-Omniscience v1.1 | Claude Opus 5.5 | 48 |
| Terminal-Bench-Science | GPT-6 Astra | 63% |
| CritPt v2 hard subset | GPT-6 Astra | 72% |
| AA-Briefcase | Claude Sonnet 5.5 | 1812 Elo |
| Terminal-Bench 4.0 | Kimi K3.1 Pro | 67% |
| AutomationBench-AA | Gemini 4 Argon | 78% |
| GDP.pdf | Muse Wonder Full | 33% all-pass |

Two splits stand out. On physics (CritPt v2), GPT-6 Astra leads at 72% on high effort while Opus 5.5, the top model overall, scores 61%. On HLE-Diamond, knowledge questions are harder than reasoning ones: Opus 5.5 and GPT-6 Astra both score 78% on reasoning, against 58% and 50% on knowledge.

## Effort and cost now matter more

The same model scores very differently depending on how much work it is allowed to do. Opus 5.5 scores 35 at low effort and 58 at max, at 10x the cost per task: $0.98 against $10.04. Claude Sonnet 5.5 now spans 29 points from low to max, up from 20 in v4.3, and GPT-6.1 Sol's spread doubles from 10 points to 20.

![Animated scene: a gauge for Claude Opus 5.5 turns from low to max as its score rises from 35 to 58 and its cost per task from $0.98 to $10.04, beside a card for GPT-6.1 Sol (max) at 55 and $1.27](https://cellcog.ai/blog/media/artificial-analysis-intelligence-index-v5/effort.svg)
*Effort moves Opus 5.5 from 35 to 58 and $0.98 to $10.04; Sol scores 55 at $1.27.*

"GPT-6.1 Sol (max) scores within 4 points of Claude Opus 5.5 (max) at about an eighth of the cost per task." Among the 10 highest-scoring models, cost per task varies by more than 13x, from GPT-6.1 Terra to Claude Fable 5.1. The tasks also got heavier: median output per Index task rose by two thirds, from 35k tokens to 59k. The four agentic tests make up 55% of the weight but a median of about 90% of output tokens, and Terminal-Bench-Science alone accounts for about a third.

## The Progress Index

Alongside v5, Artificial Analysis launched [Progress Index v1](https://artificialanalysis.ai/trends). It uses item response theory to put language models released since November 2022 on one capability scale, so a model tested on older, easier benchmarks can be compared with one tested on newer ones. The company credits Epoch AI and Anthropic for ideas it built on. The Intelligence Index remains its primary measure of the current frontier; the Progress Index is for change over time.

## What it means if you run work on these models

CellCog's Agent, Creative and Team tiers at Core and Max have run on Claude Opus 5.5 [since its release day](https://cellcog.ai/blog/cellcog-opus-5-5-day-one/), so the v5 lead is the model our AI employees already work on. The effort result matches what we see running them: the same model, asked to do more careful work, produces better work and uses more of it. That is why we [price by the work assigned](https://cellcog.ai/pricing), not by the seat. An Index task is also one task; an employee's job is many tasks that share memory, tools and context, which no single benchmark measures.

## What to watch

- Kimi K3.1 Pro's weights: once released, the top open-weights score with downloadable weights jumps from 32 to 46.
- Anthropic's next model on v5, and whether Opus 5.5's three-test lead holds; we track it in the [Opus 5.6 tracker](https://cellcog.ai/blog/claude-opus-5-6-release-date/).
- Whether labs start publishing v5 numbers at launch, now that most of it cannot be studied for.
- How the Progress Index places this year's models against GPT-4-era releases.

## FAQ

**What is the Artificial Analysis Intelligence Index?**

A composite score of model capability across tasks that reflect real use. Version 5 averages four groups with equal weight: knowledge work, coding, science and general knowledge, across nine evaluations.

**Why do private tests matter?**

A model cannot be trained on questions it has never seen. With 60% of v5 on private sets or held-out answers, a high score is harder to earn by memorizing public benchmarks.

**Which open-weights model scores highest?**

Kimi K3.1 Pro at 46, but its weights were not yet released on October 27. Among released weights, DeepSeek V4.1 Flash 1017 and GLM-5.3 tie at 32.

**What is FrontierCode 2.0?**

Cognition's private coding benchmark, launched October 27, 2026. Its 132 tasks sit in real open-source repositories and are graded on whether a maintainer would merge the change. Opus 5.5 leads it at 46% in Artificial Analysis's runs.

**What is the Progress Index?**

A second index Artificial Analysis launched the same day. It places language models released since November 2022 on one capability scale, so models years apart can be compared. The Intelligence Index stays the measure of the current frontier.

## Related

- [Coding Agent Index v2.0: Claude Opus 5.5 Leads at 61.7](https://cellcog.ai/blog/artificial-analysis-coding-agent-index/index.md)
- [GPT-6.1 Terra: $1/$5 Price, Benchmarks vs Sol and Opus](https://cellcog.ai/blog/gpt-6-1-terra/index.md)
- [Kimi K3.1 Pro: Price, Benchmarks and Open Weights Date](https://cellcog.ai/blog/kimi-k3-1-release-date/index.md)
- [Best Super Agents, Ranked With Receipts](https://cellcog.ai/blog/best-super-agents/index.md)

## The AI employee for this read

[AI Research Assistant](https://cellcog.ai/ai-employees/ai-research-assistant): I built this page. For what it covers, hire a research assistant: it reads the primary sources and cites every line.

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