General model with strong long-context, multimodal, and reasoning capability.
- Context
- 1M+
- Release
- 2026
Large Language Model Rankings
Compare leading language models by coding, writing, reasoning, math, and multimodal capability.
Snapshot updated 2026-05-20. Scores are AI Explorer normalized 0-100 ratings from public leaderboard signals.
Model data is organized from public leaderboards, provider information, and curated capability signals.
Scores normalize public signals across coding, writing, reasoning, math, and multimodal capability.
Use the LLM page to compare model strengths before choosing a provider or model family.
General model with strong long-context, multimodal, and reasoning capability.
OpenAI frontier work model for complex real-world tasks, agentic coding, research, data analysis, and cross-tool execution.
Frontier general model for complex reasoning, coding, tool use, and professional writing.
Premium model with strong writing, code review, and agentic workflow behavior.
Thinking model for complex Q&A and fresh-information workflows.
Coding-optimized model for repository-scale editing, testing, and debugging.
Balanced multilingual and coding model with broad API availability.
DeepSeek next-generation V4 family model for long-context work, coding, math reasoning, and cost-efficient production APIs.
Z.AI flagship model for long-horizon agent tasks, real-world engineering delivery, coding, and complex reasoning.
European model for enterprise API, coding, and multilingual workloads.
Z.AI GLM-5 foundation model for general reasoning, writing, coding, and agentic engineering workflows.
General model with strong long-context and Chinese-language performance.
Large open-weight model for self-hosted enterprise and research workflows.
Low-latency DeepSeek V4 variant for high-throughput, cost-sensitive, and real-time product scenarios.
Z.AI GLM-4.6 improves real-world coding, long-context processing, reasoning, search, writing, and agentic applications.
Stable model for Chinese, writing, and general knowledge tasks.
Open-weight reasoning model focused on math, coding, and cost-efficient deployment.
Open-weight MoE model for self-hosting and cost-sensitive inference.