aiqbench · LLM benchmarks

Benchmarks

Per-axis LLM benchmarks. One leaderboard, one number, one source — no fabricated composites.

Sources: 8
Entries tracked: 22,308
Last sync: 16 min16 minutes ago

All sources syncing normally

Arena · Text· 12 hours ago
Arena · WebDev· 12 hours ago
Arena · Vision· 12 hours ago
Arena · Agent· 12 hours ago
GPQA Diamond· 16 minutes ago
SWE-bench· 16 minutes ago
Terminal-Bench· 16 minutes ago
ARC-AGI-2· 16 minutes ago

Arena · Text· 12 hours ago
Arena · WebDev· 12 hours ago
Arena · Vision· 12 hours ago
Arena · Agent· 12 hours ago
GPQA Diamond· 16 minutes ago
SWE-bench· 16 minutes ago
Terminal-Bench· 16 minutes ago
ARC-AGI-2· 16 minutes ago

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Released:AfterBefore

o1

67.9%

no interval published

openaiDec 2024swing #127–#229

o1-mini

57.6%

no interval published

openaiSep 2024swing #185–#761

One grid, every column. Pick axes in the Axes panel — one axis ranks like a single board, several blend into a weighted composite, all of them read as the index. Rank is assigned before any filter and never renumbers.

Axes1 on

Ranking on 1 axis — single-board order, no blending.

same = ranks models almost identically to an axis you already selected · close = nearly so · ? = too few shared models to tell.

Overall

Ability

Industry

Arena boards

Measured benchmarks

Agentic

Safety & factuality

Language

	Model	Org				± CI	Swing	Add to compare
71	o1	openai	Dec 2024	$15 / $60	67.9%	—	#127–229
103	o1-mini	openai	Sep 2024	—	57.6%	—	#185–761

Showing LiveCodeBench (Artificial Analysis) exactly as the source published it — its own score and confidence interval, no blending. Select a second axis to build a weighted composite.

o1

o1-mini

The few things in AI and quantum that actually mattered this week — honestly summarised.