#1 of 17 models we track on the Artificial Analysis Intelligence Index, an all-round score (58 index points). Best result: #1 of 18 on LMArena WebDev (build websites & apps, 1807 Arena score). Anthropic has 2 more models on this page.
Tied #2 of 17 models we track on the Artificial Analysis Intelligence Index, an all-round score (53 index points). Best result: #1 of 15 on LMArena Text (chat & writing, 1524 Arena score). Google has 2 more models on this page.
Tied #2 of 17 models we track on the Artificial Analysis Intelligence Index, an all-round score (53 index points). Best result: #1 of 11 on ARC-AGI-2 (new puzzles, 95.0%). OpenAI has 1 more model on this page.
#7 of 17 models we track on the Artificial Analysis Intelligence Index, an all-round score (45 index points). Best result: #4 of 6 on Terminal-Bench 4.0 (agent tasks, 41.8 % of tasks done).
#8 of 17 models we track on the Artificial Analysis Intelligence Index, an all-round score (44 index points). Best result: #4 of 15 on LMArena Text (chat & writing, 1487 Arena score).
Tied #10 of 17 models we track on the Artificial Analysis Intelligence Index, an all-round score (39 index points). Best result: #1 of 4 on OpenRouter usage (this week) (most used (this week), 36.8 trillion tokens this week).
Tied #10 of 17 models we track on the Artificial Analysis Intelligence Index, an all-round score (39 index points). Best result: #6 of 16 on Output speed (speed, 131 tokens per second).
#13 of 17 models we track on the Artificial Analysis Intelligence Index, an all-round score (34 index points). Best result: #4 of 6 on GPQA Diamond (science questions, 89.2%).
#14 of 17 models we track on the Artificial Analysis Intelligence Index, an all-round score (30 index points). Best result: #3 of 16 on Output speed (speed, 228 tokens per second).
#17 of 17 models we track on the Artificial Analysis Intelligence Index, an all-round score (14 index points). Best result: #5 of 16 on Output speed (speed, 160 tokens per second).
18 AI models on 11 tests, ranked from published scores. Every number names its source.
Quick answer
No single model wins every test: Claude Opus 5.5 leads 4 of 11, Gemini 4 Argon and GPT-6 Astra lead 2 each.
18 models
11 tests
9 of 11 run by outside groups
Updated 18 Oct 2026, 12:00 IST
Open vs closed
Open = you can download the model. Closed = you can only use it through the maker's app or paid API.
Open-weight models handled the most text-model tokens on OpenRouter this week. Closed models still lead the independent boards we track (10 of 11 measures).
Best open model vs best closed model, per test
Job
Best open
Best closed
Gap
All-roundArtificial Analysis Intelligence Index · index points
OpenMiMo-V2.6-ProXiaomi · MIT: free for almost any use46
Run it yourself. 9 of the 18 models we track have open weights: you can download them and run them on your own computer or server, so your data stays with you (the biggest ones need a powerful machine). 5 of them use MIT or Apache 2.0, free for almost any use.
Price per million tokens (closed is cheaper here). Cheapest open model with a listed price: DeepSeek-V4.1-Flash: $0.3 in / $1.2 out. Cheapest closed: GPT-6 Luna and Claude Haiku 5.5: $0.1 in / $0.5 out. Only 1 of the 9 open models list a price; the rest you run yourself or through a host you pick.
Best open-weight vs best closed model among the models we track, per test. Updated 18 Oct 2026. Each row's source and date: Sources.
Scoreboard
Every model on every test with 3 or more models. Greener = better rank.
Stronger green = better rank on that test. Bold underlined = top score. – = no published score.
Rows are sorted by top-3 finishes. Tap a test name for its full ranking and source, or a model for everything we know about it.
Each column is its own test with its own scale, so do not compare numbers across columns.
Value picks
Price, memory and the newest release.
Cheapest to useGPT-6 Luna and Claude Haiku 5.5$0.1 in per million tokensGPT-6 Luna: $0.1 in / $0.5 out · price source · Claude Haiku 5.5: $0.1 in / $0.5 out · price source
Default view with style control. Each score has a plus or minus range, so models within about 10 points are close to tied. Each model's best listed setting is used.
Build websites & appsLMArena WebDevClaude Opus 5.51807 Arena score
When people ask two AIs to build the same website or app and compare the results, which one do they pick?
Higher is better · 18 models · independent · bars start at 1237, not 0
Maker's own numbers, run with different settings, so compare with care. Close to saturated at the top and questioned for possible training leaks. Anthropic's figures are whole numbers from its cost guide.
Hardest examHumanity's Last Exam (no tools)Claude Opus 5.564.4%
2,500 expert questions written to be too hard for AI, answered without web search or code.
The official leaderboard lists none of these models yet, so these are the makers' own numbers, graded by different judges. Some answers in the test are disputed.
New puzzlesARC-AGI-2GPT-6 Astra95.0%
New picture puzzles a model has never seen, so it has to reason instead of remember. Harder for AI than for people.
Scores depend on the agent program used (Claude Code, Codex, Grok Build), listed in each score's variant. Each has a plus or minus range of about 3 points.
Most used (this week)OpenRouter usage (this week)DeepSeek-V4.1-Flash36.8 trillion tokens this week
How much developers actually use each model through OpenRouter, a popular service that connects apps to many AI models.
Higher is better · 4 models · independent
1DeepSeek-V4.1-FlashOpen weights. License: MIT: free for almost any use36.8 trillion tokens this week
What a benchmark is: a fixed test, like an exam, that every model takes so you can compare them on the same questions.
Maker's own numbers can be biased: a company picks the tests it does well on. Scores tagged "independent" were run by an outside group.
Ranks change fast: new models come out every few weeks, so check the "as of" date on each test.
One number never tells the whole story: price, speed, privacy and how a model feels to use matter too. Try two or three on your own tasks.
What we left out on purpose
Vision: no trusted vision score covers these models yet, so vision is left out.
Left out on purpose: SWE-bench and Aider (none of these models on the official boards yet), a maker's number for a rival's model, and averages we would have to compute ourselves.
Sources (9 pages)
Updated 18 Oct 2026, 12:00 IST. Scores and prices come only from these pages and each model's own source links above: