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: 26 min26 minutes ago

All sources syncing normally

Arena · Text· 9 hours ago
Arena · WebDev· 9 hours ago
Arena · Vision· 9 hours ago
Arena · Agent· 9 hours ago
GPQA Diamond· 26 minutes ago
SWE-bench· 26 minutes ago
Terminal-Bench· 26 minutes ago
ARC-AGI-2· 26 minutes ago

Arena · Text· 9 hours ago
Arena · WebDev· 9 hours ago
Arena · Vision· 9 hours ago
Arena · Agent· 9 hours ago
GPQA Diamond· 26 minutes ago
SWE-bench· 26 minutes ago
Terminal-Bench· 26 minutes ago
ARC-AGI-2· 26 minutes ago

Filter this table

Jump to a model's profile

Filter by org:

Released:AfterBefore

glm-4.6

59.6%

no interval published

Z.AIDec 2025swing #98–#398

glm-4.6v

45.4%

no interval published

Z.AIDec 2025swing #146–#679

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
116	glm-4.6	Z.AI	Dec 2025	$0.30 / $0.90	59.6%	—	#98–398
193	glm-4.6v	Z.AI	Dec 2025	$0.30 / $0.90	45.4%	—	#146–679

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

glm-4.6

glm-4.6v

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