183 models ranked for scientific research. Scored with bonuses for reasoning (complex analysis), large context (papers), vision (diagrams), web search (literature), and JSON mode (structured data).
| # | Model | Score |
|---|---|---|
| 1 | Claude Opus 4.7 (Fast)Anthropic | 95 |
| 2 | Claude Opus 4.7Anthropic | 95 |
| 3 | GPT-5.5OpenAI | 93 |
| 4 | Gemini 3.1 Pro Preview Custom ToolsGoogle | 92 |
| 5 | Gemini 3.1 Pro PreviewGoogle | 92 |
| 6 | GPT-5.4 ProOpenAI | 92 |
| 7 | GPT-5.4OpenAI | 92 |
| 8 | GPT-5.5 ProOpenAI | 91 |
| 9 | GPT-5.2 ProOpenAI | 91 |
| 10 | Claude Opus 4.6 (Fast)Anthropic | 90 |
| 11 | Claude Opus 4.6Anthropic | 90 |
| 12 | Grok 4.20xAI | 89 |
| 13 | GPT-5.3-CodexOpenAI | 89 |
| 14 | GPT-5 ProOpenAI | 89 |
| 15 | Gemini 3 Flash PreviewGoogle | 88 |
| 16 | Grok 4xAI | 88 |
| 17 | Grok 4.20 Multi-AgentxAI | 88 |
| 18 | GPT-5.1-Codex-MaxOpenAI | 88 |
| 19 | GPT-5.2-CodexOpenAI | 90 |
| 20 | GPT-5.2OpenAI | 90 |
| 21 | o3 Deep ResearchOpenAI | 87 |
| 22 | o3 ProOpenAI | 87 |
| 23 | o3OpenAI | 87 |
| 24 | Claude Sonnet 4.6Anthropic | 85 |
| 25 | Claude Opus 4.5Anthropic | 85 |
| 26 | GPT-5 CodexOpenAI | 88 |
| 27 | GPT-5OpenAI | 88 |
| 28 | GPT-5.1OpenAI | 87 |
| 29 | GPT-5.1-CodexOpenAI | 87 |
| 30 | GPT-5.1-Codex-MiniOpenAI | 87 |
Large context models (128K+) can process entire research papers. Combined with reasoning, they extract key findings, identify methodology gaps, and synthesize across multiple sources.
Vision models analyze charts, plots, and experimental images. Reasoning models work through complex statistical analyses, helping researchers validate findings and spot patterns.
Reasoning models help design experiments, identify confounding variables, and suggest controls. Web search keeps research informed by the latest published methods and protocols.
Large output models draft sections of scientific papers with proper structure. Models review drafts for logical consistency, suggest improvements, and check against current literature.
Models perform literature reviews (processing hundreds of papers via large context), generate hypotheses, design experiments, and analyze results. Web search accesses the latest publications. Reasoning handles complex scientific reasoning and mathematical derivations.
Models draft methods sections, results descriptions, and discussion points. They format citations, generate abstracts, and structure arguments for grant proposals. Large output generates complete drafts without truncation. Always verify claims against primary sources.
Reasoning for mathematical modeling and algorithm design. Code generation for simulation scripts (Python, MATLAB, Julia). Large context for processing datasets and multiple papers simultaneously. JSON mode for structured experimental data output.
Models perform statistical analysis, generate visualizations, identify outliers, and suggest additional experiments. They understand p-values, confidence intervals, and effect sizes. Reasoning helps interpret results in the context of existing literature.