The Best EQ-Bench Alternatives in 2026

DeepSWE benchmarks coding agents on long-horizon software engineering tasks and publishes a leaderboard.

SWE-bench publishes benchmark leaderboards for evaluating software engineering agents.

BlockSurvey creates privacy-first forms and surveys with end-to-end encrypted responses, plus AI-assisted question writing.

RankedAGI compares AI models using benchmarks including SWE Bench, Codeforces, LMSYS, and LiveBench.

MathArena evaluates language models using math benchmarks and publishes model results.

Kaggle Benchmarks lets users build, run, and share evaluations of AI models and agents.

Context Arena provides a leaderboard for evaluating language models on long-context tasks.

Alison.ai analyzes advertising creatives and provides creative scores, predictive insights, and competitor benchmarks for brands and agencies.

VBench lets users upload model evaluation files to update a video generation benchmark.

OpenRouter publishes language model rankings based on real usage through its API.

LifeArchitect publishes a reference table of language models and their specifications and data points.

Indico benchmarks language models on extractive, classification, and predictive tasks.

Deploybase compares GPU cloud and language model API prices, performance benchmarks, and provider market data.

Artificial Analysis compares AI models and API providers using benchmarks for quality, price, speed, and latency.

OpenLM Arena compares open language models through leaderboards and benchmark results.

Explore leaderboards with expert-driven LLM benchmarks and updated AI model rankings across coding, reasoning and more.

This article discusses challenges in evaluating language models and interpreting benchmark results.

Aider LLM Leaderboards compares language models on code editing benchmarks.

VoxelBench benchmarks language models on creating voxel builds from prompts.

The Hugging Face Open LLM Leaderboard compares language models across evaluation tests including IFEval, MATH, and MMLU-Pro.

WhichLLM tests local language models on a user’s hardware and ranks them using recent benchmarks.

skill-optimizer benchmarks, evaluates, and optimizes skills to check their performance across large language models.

LLMeBench provides a flexible framework for benchmarking large language models.