Every large model,
Measured on one ruler

30 production models' intelligence, scientific reasoning, terminal agents, price and speed, all side by side in one table. No vendor-reported numbers, and every column carries its source and methodology version.

Updated 2026-11-04 Intelligence v5 · 2026-10-27 Indexed 30 models Benchmarks 6
Models indexed
30
In v5 index
20
Benchmarks
6
Open-weight models
13

Overall leaderboard

Full ranking →

Ranked by the Artificial Analysis Intelligence Index v5 — currently the only independent composite index that covers closed and open models and refreshes every two weeks.

# Model v5 Percentile GPQA TB 4.0 Input Output tok/s
1 Gemini 4 CarbonGoogle 60.0 100% — 65.2 $4.00 $20.00 88
2 Claude Opus 5.5Anthropic 59.1 98% 93.9 59.6 $4.00 $20.00 94
3 GPT-6 AstraOpenAI 56.9 95% 95.8 59.1 $10.00 $50.00 81
4 GPT-6.1 SolOpenAI 54.6 91% 95.4 56.1 $2.00 $10.00 77
5 Claude Sonnet 5.5Anthropic 54.5 91% 95.6 63.6 $2.00 $10.00 135
6 GPT-6.1 TerraOpenAI 51.3 86% 94.3 55.6 $1.00 $5.00 94
7 Gemini 4 ArgonGoogle 50.4 84% 96.4 57.1 $2.00 $10.00 80
8 Muse Wonder FullMeta 50.0 83% — — — — —
9 Claude Fable 5.1Anthropic 49.0 82% — 52.0 $10.00 $50.00 57
10 Kimi K3.1 Pro Open weightsMoonshot AI 46.0 77% — 67.2 $2.00 $10.00 28
11 Muse WonderMeta 44.0 73% — — $4.00 $20.00 143
12 Claude Haiku 5.5Anthropic 36.0 60% — — $0.10 $0.50 235
GPQA measures graduate-level science reasoning out of 100; TB 4.0 is the task completion rate for terminal agents. Prices are USD per million tokens. A dash means the benchmark has no published result for that model.

Price × intelligence: who is overrated

Price analysis →

The x-axis is blended price (3:1 input/output weighting, log scale); the y-axis is the intelligence index. Top-left is cheap and smart, bottom-right is expensive and not that smart.

Filled dot = closed API · hollow dot = open weights · dot size = intelligence score

Rankings by dimension

Methodology →

A composite score hides real differences. The same model can match the flagship on document generation and score 1% on terminal agents — pick on the dimension you care about.

Editor's notes

The five things in the last month of data that actually matter.

01

The intelligence index changed its ruler

The AA Intelligence Index moved to v5 on 27 October and every model's score shifted down. DeepSeek V4.1 Flash went from 45.1 on v4.3.2 to 33.0 on v5 — not because it got worse, but because the questions got harder. Comparing across versions is the most common misreading of rankings like this.

02

The middle of the market collapsed to $2/$10

GPT-6.1 Sol, Claude Sonnet 5.5, Kimi K3.1 Pro and Gemini 4 Argon now cost the same. Two years ago this tier was $15/$75. Price no longer signals which tier a model is in — only score and speed do.

03

Open weights take the agent crown

The day Kimi K3.1 Pro's weights opened (11-04), the top of Terminal-Bench 4.0 (67.2%) became an open-weights model; the best closed one, Gemini 4 Carbon, sits at 65.2%. Open models still trail by 3 points on knowledge — on getting work done they have already overtaken.

04

A 4.8× speed gap at the same price

Claude Sonnet 5.5 and Kimi K3.1 Pro both cost $2/$10, but output at 135 vs 28 tok/s. For a 4,000-character answer that is 30 seconds versus two and a half minutes.

05

Promo pricing has an expiry date

Gemini 4 Carbon's $2/$10 launch promo has ended and it now lists at $4/$20; Gemini 4 Argon's promo price doubles on 2026-12-01; Gemini 3.8 Flash's $0.75/$3.75 doubles on 2027-01-01. Budgeting at today's prices will mislead you.

06

You can't compute value per dollar for a subscription model

The newly catalogued Muse Wonder Full scores 50.0 on v5 — six points above the standard Wonder at 44.0, and six below its own v4.3.2 score of 56.0. But it is sold only inside the Muse Code subscription at $50 / $200 a month, with no token-priced API, so it enters the leaderboard and stays out of the price table. Comparing a subscription model with API models on points per dollar produces a number that means nothing.

9,945 billion tokens network-wide on 2026-11-04, versus the previous session -0.17%. Read daily call volume like a stock: rising volume on the way up means share is being taken, falling volume on the way down means a model is being replaced.

AI directory

All 103 →

The rankings answer "which model is best"; the directory answers "which one can I use right now". 103 sites in 12 categories, each flagged for free tier and overseas access.

Pick a model by use case

Tools →

You need the strongest reasoning

Among closed models look at Claude Opus 5.5 (v5 59.1) and Gemini 4 Argon (GPQA 96.4). On the open side only Kimi K3 comes close at GPQA 93.1.

Reasoning ranking →

You need it to change code

Terminal-Bench 4.0 is the only honest metric here. Any model below 20% should not go near a CI pipeline.

Coding ranking →

You need the lowest possible cost

DeepSeek V4.1 Flash buys 62 intelligence points per dollar — 8.5× Opus 5.5 — under an MIT licence you can self-host.

Cost-efficiency ranking →