Model Comparison Calculator
Compare AI model pricing, context windows, and capabilities side by side. Select 2–4 models to compare.
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2 of 4 selected
Alibaba
Anthropic
Cohere
DeepSeek
Meta
Mistral
OpenAI
Perplexity
xAI
| Metric | GPT-5.4 OpenAI | Claude Sonnet 4.6 Anthropic |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Context Window | 1M★ | 1M★ |
| Max Output | 128K★ | 64K |
| Input / 1M tokens | $2.50★ | $3.00 |
| Output / 1M tokens | $15.00★ | $15.00★ |
| Tokenizer | GPT (exact) | Estimate |
GPT-5.4
OpenAI
Claude Sonnet 4.6
Anthropic
★Best value in each category among selected models
Frequently Asked Questions
Which AI model is the cheapest?
As of 2026, the cheapest models by input token cost include Llama 3.1 8B via Groq ($0.05/1M), Gemini 3.1 Flash-Lite ($0.25/1M), and DeepSeek V3.2 Chat ($0.28/1M). For output tokens, Llama 3.1 8B is also the lowest at $0.08/1M. Keep in mind that the cheapest model isn't always the best fit — context window size, output quality, speed, and rate limits all affect real-world cost.
What is a context window?
A context window is the maximum number of tokens a model can process in a single request, including both your input (prompt, documents, conversation history) and the model's output. A 1M token context window holds roughly 750,000 words — about 10 full-length novels. Larger windows let you process longer documents and maintain longer conversations, but very large contexts can increase latency and cost.
How do I choose between different AI models?
Consider four key factors: Cost — compare input and output prices per 1M tokens scaled to your expected usage. Context window — make sure the model fits your longest prompts and documents. Output limit — for generation tasks, check max output tokens; some models cap at 8K even with large context windows. Capability tier — flagship models like Claude Opus or GPT-5.4 outperform smaller models on complex reasoning tasks but cost significantly more. For most production workloads, a mid-tier model balances quality and cost well.