LLM Model Comparison — May 2026
Side-by-side comparison of Claude 4.6, GPT-4o, Gemini 2.5, Llama, and Mistral across pricing, context windows, and capabilities.
2026 LLM Pricing Comparison Table
The LLM landscape in 2026 spans five major providers with over 20 distinct models. Prices vary by more than 100x between the cheapest and most expensive options, making model selection one of the most consequential engineering decisions for AI-powered products. The table below covers the most relevant models for production use.
| Model | Provider | Input / 1M | Output / 1M | Context |
|---|---|---|---|---|
| Claude Opus 4.7 | Anthropic | $5.00 | $25.00 | 1M |
| Claude Sonnet 4.6 | Anthropic | $3.00 | $15.00 | 1M |
| Claude Haiku 4.5 | Anthropic | $1.00 | $5.00 | 200K |
| GPT-4o | OpenAI | $2.50 | $10.00 | 128K |
| GPT-4o mini | OpenAI | $0.15 | $0.60 | 128K |
| GPT-4 Turbo (legacy) | OpenAI | $10.00 | $30.00 | 128K |
| Gemini 2.5 Pro | $1.25 | $10.00 | 1M | |
| Gemini 2.5 Flash | $0.30 | $2.50 | 1M | |
| Gemini 2.5 Flash-Lite | $0.10 | $0.40 | 1M | |
| Llama 3 70B | Groq | $0.59 | $0.79 | 8K |
| Llama 3 8B | Groq | $0.05 | $0.08 | 8K |
| Mixtral 8x22B | Mistral | $2.00 | $6.00 | 64K |
| Mistral Large | Mistral | $4.00 | $12.00 | 32K |
Choosing the Right Model for Your Use Case
No single model is best for every task. The right choice depends on your quality requirements, latency tolerance, budget constraints, and specific use case. Here is how to think about model selection by workload type.
Customer support chatbots need fast responses, reasonable quality, and low per-conversation cost. Claude Haiku 4.5 or GPT-4o mini are ideal for simple FAQ handling at under $0.01 per conversation. For complex support requiring multi-step reasoning, Claude Sonnet 4.6 or GPT-4o justify their higher cost with significantly better resolution rates.
Code generation and review demands high reasoning capability. Claude Sonnet 4.6 and GPT-4o are the leading choices, with Claude showing particular strength in understanding large codebases and maintaining consistency across long files. For code completion and simple boilerplate, GPT-4o mini or Llama 3 70B deliver acceptable quality at a fraction of the cost.
Document processing and RAG pipelines involve high input token volumes. Context window size matters here: Gemini 2.5 Pro, Claude Opus 4.7, and Claude Sonnet 4.6 all support 1M token context. For cost-per-document, GPT-4o's lower input price ($2.50 vs $3 for Claude Sonnet 4.6) adds up at scale. If your documents fit within 8K tokens, Groq's Llama 3 70B offers exceptional value.
Content generation at scale benefits from output-heavy pricing. Gemini 2.5 Flash-Lite at $0.40 per million output tokens is the cheapest option for generating large volumes of text, though quality may require post-processing. For marketing copy, blog posts, and email drafts where quality matters, Claude Sonnet 4.6 offers the best balance of cost and coherence.
Context Window Comparison
Context window size determines how much text a model can process in a single request. This is critical for applications that need to analyze long documents, maintain extended conversation history, or process entire codebases. Gemini 2.5 Pro, Claude Opus 4.7, and Claude Sonnet 4.6 all support 1 million token context windows, enough to process approximately 750,000 words or a 3,000-page book in a single request. GPT-4o supports 128K tokens, while open-source models like Llama 3 are limited to 8K tokens unless extended through custom implementations. Larger context windows consume more input tokens, so the cost implications are significant for document-heavy workloads. A single Claude Sonnet 4.6 request using the full 1M context window costs $3.00 in input tokens alone.
Frequently Asked Questions
Which LLM is the best value for money in 2026?
GPT-4o offers excellent value at $2.50/$10 per million tokens. Claude Sonnet 4.6 at $3/$15 offers stronger coding quality. For budget-constrained projects, GPT-4o mini ($0.15/$0.60) and Gemini 2.5 Flash ($0.30/$2.50) deliver strong quality at minimal cost.
What is the largest context window available in 2026?
Google Gemini 2.5 Pro, Claude Opus 4.7, and Claude Sonnet 4.6 all support 1 million token context windows. GPT-4o supports 128K tokens. Larger context windows allow processing entire codebases or books in a single request.
Should I use an open-source or proprietary LLM?
Use proprietary APIs (Claude, GPT-4) when you need the highest quality and can tolerate per-token costs. Use open-source models (Llama, Mistral) when you need data privacy, have high volume (over $2,000/month API spend), or need to fine-tune the model for your domain.
Which LLM is best for code generation?
Claude Sonnet 4.6 and GPT-4o are the top performers for code generation. Claude Sonnet 4.6 excels at understanding large codebases and writing production-quality code. For budget code tasks, GPT-4o mini and Llama 3 70B perform well on straightforward coding tasks.
How do I choose between Claude, GPT-4o, and Gemini?
Choose Claude Sonnet 4.6 for code generation, long documents, and nuanced instruction following. Choose GPT-4o for cost-effective multimodal tasks and broad general knowledge. Choose Gemini 2.5 for massive context windows (1M+ tokens) and Google Cloud integration. Each excels in different areas.
Related Guides
Built by Michael Lip. Pricing data updated regularly from official provider pages.