The top AI models for research, ranked by a research-weighted composite score. Models are scored with bonuses for large context windows (processing full papers), web search (finding and citing sources), reasoning (complex analysis), and vision (reading charts and figures). Updated hourly from 365+ models.
339
Total Models
72
Web Search
190
With Reasoning
278
128K+ Context
33
Free Models
| # | Model | Score |
|---|---|---|
| 1 | Claude Opus 4.7Anthropic | 126 |
| 2 | GPT-5.5OpenAI | 124 |
| 3 | Gemini 3.1 Pro Preview Custom ToolsGoogle | 123 |
| 4 | Gemini 3.1 Pro PreviewGoogle | 123 |
| 5 | GPT-5.4 ProOpenAI | 123 |
| 6 | GPT-5.4OpenAI | 123 |
| 7 | GPT-5.5 ProOpenAI | 122 |
| 8 | GPT-5.2 ProOpenAI | 122 |
| 9 | Claude Opus 4.6 (Fast)Anthropic | 121 |
| 10 | Claude Opus 4.6Anthropic | 121 |
| 11 | Grok 4.20xAI | 120 |
| 12 | GPT-5.3-CodexOpenAI | 120 |
| 13 | GPT-5 ProOpenAI | 120 |
| 14 | Gemini 3 Flash PreviewGoogle | 119 |
| 15 | Grok 4xAI | 119 |
| 16 | Grok 4.20 Multi-AgentxAI | 119 |
| 17 | GPT-5.1-Codex-MaxOpenAI | 119 |
| 18 | o3 Deep ResearchOpenAI | 118 |
| 19 | o3 ProOpenAI | 118 |
| 20 | o3OpenAI | 118 |
| 21 | Claude Sonnet 4.6Anthropic | 116 |
| 22 | Claude Opus 4.5Anthropic | 116 |
| 23 | Gemini 2.5 ProGoogle | 115 |
| 24 | Gemini 2.5 Pro Preview 06-05Google | 115 |
| 25 | Gemini 2.5 Pro Preview 05-06Google | 115 |
| 26 | Claude Sonnet 4.5Anthropic | 113 |
| 27 | Claude Opus 4Anthropic | 113 |
| 28 | GPT-5.2-CodexOpenAI | 113 |
| 29 | GPT-5.2OpenAI | 113 |
| 30 | o4 Mini Deep ResearchOpenAI | 112 |
AI models with large context windows can ingest entire research papers and produce structured summaries. Feed in a 50-page PDF and get key findings, methodology, and limitations extracted in seconds. Models with 128K+ context handle even the longest papers without chunking.
Models with web search can look up citations in real time, verify claims against published sources, and find the latest papers on a topic. This dramatically reduces the time spent on manual source checking and helps surface relevant work you may have missed.
Reasoning-capable models excel at statistical analysis, interpreting experimental results, and identifying patterns in research data. They can help with hypothesis formulation, methodology critique, and drawing nuanced conclusions from complex datasets.
Vision-capable models can read charts, figures, tables, and diagrams directly from research papers. Combined with large context windows, these models can process multi-page documents with mixed text and visual content - ideal for systematic reviews and meta-analyses.
Discover models by specific research capabilities, or compare top models head-to-head on the full leaderboard.
Models with web search capabilities and large context windows excel at research synthesis. Claude and GPT-4o with web search can cross-reference multiple sources and identify contradictions. For academic research, models with citation capabilities help verify claims against primary sources.
AI accelerates literature reviews by summarizing papers, identifying themes, and finding connections across studies. Models with 128K+ context can process multiple full papers simultaneously. However, they may miss nuanced methodological issues - use them for initial survey, then deep-read key papers yourself.
Models with web search analyze competitor websites, press releases, and market data in real-time. Function-calling models can query multiple data sources systematically. Best results come from structured prompts that specify exactly what competitive dimensions to analyze and compare.
Reasoning models (o3, DeepSeek R1) excel at technical analysis requiring logical deduction. For broad scientific literature, models with large training data cutoffs and web search provide more current information. Domain-specific fine-tuned models outperform general models for specialized fields like biomedicine or materials science.