Last updated: April 5, 2026 | Reviewed by Daniel Ashford

The LLM Judge Index

Independent, multi-dimensional AI model evaluation by Daniel Ashford. 12 models ranked. Methodology

#ModelIndexPriceTrend
1
👑 Claude Opus 4Anthropic
96.0$15+12
2
🔥 GPT-5.3 CodexOpenAI
95.2$10+8
3
Claude Sonnet 4Anthropic
93.2$3+15
4
Gemini 2.5 UltraGoogle
93.0$7+5
5
GPT-4oOpenAI
91.0$2.5-2
6
🆓 Llama 4 405BMeta
87.8Free+22
7
Mistral Large 3Mistral
87.8$4+6
8
Qwen 3.5 PlusAlibaba
86.2$2+18
9
💰 DeepSeek V3DeepSeek
85.5$0.55+31
10
Claude Haiku 4.5Anthropic
85.5$0.8+4
11
Gemini 2.5 FlashGoogle
82.5$0.15+9
12
GPT-4o MiniOpenAI
80.5$0.15-1

Best LLM By Use Case

💻
Best for Code Generation
Weighted ranking
💬
Best for Customer Chatbot
Weighted ranking
✍️
Best for Content Writing
Weighted ranking
📊
Best for Data Analysis
Weighted ranking
🔬
Best for Research & RAG
Weighted ranking
🛡️
Best for Safety-Critical
Weighted ranking

Best LLM By Industry

🎓
Education
Schools, tutoring and edtech
🏥
Healthcare
Hospitals, clinics and health tech
🏦
Financial Services
Banking, investment and fintech
⚖️
Legal
Law firms, contracts and legal tech
💬
Customer Support
Help desks, chatbots and CX

Popular Comparisons

Claude Opus 4 vs GPT-5.3 Codex
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Claude Opus 4 vs Claude Sonnet 4
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Claude Opus 4 vs GPT-4o
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Claude Opus 4 vs Llama 4 405B
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Claude Opus 4 vs Mistral Large 3
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Claude Opus 4 vs Qwen 3.5 Plus
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Claude Opus 4 vs DeepSeek V3
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LLM Glossary

47 AI and language model terms explained. Browse all

Large Language Model (LLM)
An AI system trained on massive text data to understand and generate human language.
Tokens
The basic units of text that LLMs process — roughly 3/4 of a word.
Context Window
The maximum amount of text an LLM can process in a single request.
Hallucination
When an LLM generates plausible-sounding but factually incorrect information.
Inference
The process of an LLM generating a response to your input.
Prompt
The text input you send to an LLM to get a response.
Fine-Tuning
Customizing a pre-trained LLM on your specific data to improve performance for your use case.
RAG (Retrieval-Augmented Generation)
A technique that gives LLMs access to external documents to improve accuracy and reduce hallucination.

By Provider

Anthropic (3)OpenAI (3)Google (2)Meta (1)Mistral (1)Alibaba (1)DeepSeek (1)