AI Leaderboard — Compare 300+ Top AI Models by Intelligence, Speed & Price

On the LLM Stats Leaderboard, GPT-5.6 Sol currently leads on GPQA Diamond (94.6% gpqa), the most discriminating reasoning benchmark at the frontier. This AI leaderboard ranks models by the LLM Stats Score, which aggregates GPQA, SWE-Bench Verified, coding-arena performance and pricing into one comparable AI ranking. Rankings refresh continuously as new benchmark results land.

"Best" depends on what you're optimizing for. For frontier reasoning, GPT-5.6 Sol leads on GPQA. For coding agents, Claude Opus 5 is the strongest in head-to-head coding-arena play. For low cost at frontier quality, Grok 4.5 is the cheapest in the top 10 at $2.00 /M tok. The leaders summary above the table names the current winner per axis.

The leading LLMs in 2026 are GPT-5.6 Sol, Claude Opus 5, and the frontier models from OpenAI (GPT-5 family), Anthropic (Claude Opus and Sonnet), Google (Gemini 3 Pro), xAI (Grok 4), DeepSeek (V3 / R1) and Z.AI (GLM-5). Open-weights leaders include Llama, Qwen and DeepSeek. The full ranking is in the leaderboard table above.

Grok 4.5 is the cheapest model in the top 10 by GPQA Diamond, at $2.00 /M tok input. The Cheapest filter on the leaderboard restricts to verified, currently-available frontier models — pricing is pulled from each provider's public price list and cross-checked against billing samples through the LLM Stats proxy.

Grok-4 Fast Reasoning currently exposes the largest practical context window at 2.0M tokens tokens. Larger context lets you keep more documents, conversation history and tool traces in a single request. For long-document workloads, also consult the per-model "effective context" notes on each model detail page — providers vary in how well they actually use the upper end of their advertised windows.

Gemini 3.7 Flash currently has the highest output throughput at 595 tok/s. Output speed is measured by routing standardized prompts through each provider's API and averaging tokens-per-second over a 7-day rolling window. Fast inference matters most for streaming chat UIs and agentic loops; for batched async workloads, blended price per 1M tokens is usually the better axis.

Kimi K3 currently leads among open-weights LLMs (93.5% gpqa). The open-weights ecosystem is dominated by Llama, Qwen, DeepSeek, Mistral, GLM and Gemma. The dedicated Open LLM Leaderboard filters this catalog to models with publicly released weights so you can self-host or fine-tune.

The LLM Stats Score is a composite that blends verified benchmark results (GPQA Diamond, SWE-Bench Verified, coding-arena), live performance metrics (output throughput, time-to-first-token) and per-token pricing into one comparable number. Pricing and metadata revalidate hourly; live performance updates on a 7-day rolling average. For the full weighting and refresh cadence see the LLM Stats Score methodology. 359 canonical models are tracked across every major lab and inference provider.