Every frontier model. One place.
Compare 19 production models across OpenAI, Anthropic, Google, SpaceXAI (xAI), Moonshot, Alibaba, Z.ai, Xiaomi, DeepSeek and MiniMax — on benchmarks, pricing, context, and practical task fit. Pick a model in 30 seconds, or evaluate a real task in two minutes.
Quick pick
Three questions — one recommended model. For nuanced tradeoffs, use the full evaluator below.
The full lineup
Click any card to see strengths, watch-outs, and tooling. Pin up to 3 to compare side-by-side.
Side-by-side comparison
Pinned models compared across the dimensions that matter most.
Task evaluator
Paste a real task, choose the dominant work type, and tune cost, speed, and context sensitivity. Scored against all 19 production models.
Recommendation
Relative fit score across all 19 production models — higher is better, and keyword matches in your task can push it above 100. Top 5 shown with tradeoff rationale.
Side-by-side prompt runners
Top 3 recommended models get starter prompts. Paste into vendor consoles or OpenRouter and score outputs consistently.
Scorecards
Repeatable rubric for head-to-head runs.
Best team of models
Splits a workflow into subtasks and assigns the best model for each slice — routing across the full 19-model set.
Routed plan
Opinionated defaults — override freely.
Ones to watch
Models that are announced, restricted or still in preview — plus two open-source agent harnesses you can adopt now. Worth tracking closely.
How to use this in practice
Start with the quick pick. For zero-cost experiments, try Qwen3.8-27B (free OpenRouter tier) or self-host Gemma 4 / GLM-5.3-Flash before paying for frontier models, and use the router for compound workflows. Compare cost per finished task, not per-token price — Grok 4.7 and Sonnet 5.5 at max effort show how the same sticker price can double the bill. Watch: Gemini 4 Argon and Claude Haiku 5.5 are the next likely shake-ups; near-frontier pricing has converged at ~$2/$10 (GPT-6.1 Sol, Sonnet 5.5), and the open-weight lead now sits with MiMo-V2.6-Pro, GLM-5.3 and Qwen3.8.