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AI for Science

242 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).

How we rank: composite score (benchmark scores 90%, capabilities 5%, context window 5%) adjusted with use-case-specific capability bonuses.
242
Total Ranked
242
Reasoning
167
Vision
237
128K+ Context

Science AI - Ranked by Science Score

#ModelScore
1Claude Fable 5Anthropic97
2Claude Fable 5 (batch)Anthropic97
3Claude Opus 5 (Fast)Anthropic95
4Claude Opus 5Anthropic95
5Claude Opus 4.8 (Fast)Anthropic95
6Claude Opus 4.8Anthropic95
7Claude Opus 4.7 (Fast)Anthropic95
8Claude Opus 4.7Anthropic95
9Claude Opus 4.7 (batch)Anthropic95
10Claude Opus 4.8 (batch)Anthropic95
11GPT-5.5 ProOpenAI93
12GPT-5.5 Pro (batch)OpenAI93
13GPT-5.5OpenAI93
14GPT-5.5 (batch)OpenAI93
15Gemini 3.1 Pro Preview Custom ToolsGoogle92
16Gemini 3.1 Pro PreviewGoogle92
17Gemini 3.1 Pro Preview (batch)Google92
18GPT-5.4 ProOpenAI92
19GPT-5.4 Pro (batch)OpenAI92
20GPT-5.4OpenAI92
21GPT-5.4 (batch)OpenAI92
22GPT-5.3-CodexOpenAI91
23GPT-5.2-CodexOpenAI91
24GPT-5.2 ProOpenAI91
25GPT-5.2 Pro (batch)OpenAI91
26GPT-5.2OpenAI91
27GPT-5.2 (batch)OpenAI91
28Claude Opus 4.6Anthropic90
29Claude Opus 4.6 (batch)Anthropic90
30GPT-5.6 Luna ProOpenAI89

AI in Scientific Research

Literature Review & Analysis

Large context models (128K+) can process entire research papers. Combined with reasoning, they extract key findings, identify methodology gaps, and synthesize across multiple sources.

Data Analysis & Visualization

Vision models analyze charts, plots, and experimental images. Reasoning models work through complex statistical analyses, helping researchers validate findings and spot patterns.

Experiment Design

Reasoning models help design experiments, identify confounding variables, and suggest controls. Web search keeps research informed by the latest published methods and protocols.

Paper Writing & Review

Large output models draft sections of scientific papers with proper structure. Models review drafts for logical consistency, suggest improvements, and check against current literature.

Frequently Asked Questions

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.

AI for Science - Best AI Research Models | LM Market Cap