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Anthropic Claude vs Chatgpt 4o Latest

This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.

Anthropic

Model

Anthropic Claude

Context window

100K

100,000 tokens · ~75K words

Model page
Openai

Model

Chatgpt 4o Latest

Image inputTool calling

Context window

128K

128,000 tokens · ~96K words

Model page

Context window · side by side

Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.

Anthropic Claude100K
Chatgpt 4o Latest128K

Chatgpt 4o Latest has about 1.3× the context window of the other in this pair.

Chatgpt 4o Latest has 28% more context capacity (128K vs 100K tokens). Chatgpt 4o Latest is 37% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Chatgpt 4o Latest. Its 128K context fits entire documents without chunking (vs 100K).

  • RAG / high-volume retrieval

    Use Chatgpt 4o Latest. Input tokens are 37% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Anthropic Claude. Its 8K max output lets you generate complete artifacts in one request.

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

SpecAnthropic ClaudeChatgpt 4o Latest
Context window100,000 tokens (100K)128,000 tokens (128K)
Max output tokens8,191 tokens (8K)4,096 tokens (4K)
Speed tierBalancedBalanced
VisionNoYes
Function callingNoYes
Extended thinkingNoNo
Prompt cachingNoNo
Batch APIYesYes
Release dateN/AN/A

Pricing matrix

Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.

ProviderAnthropic Claude inAnthropic Claude outChatgpt 4o Latest inChatgpt 4o Latest out
Aws Bedrock$8.00/M$24.00/M
Openai$5.00/M$15.00/M

Frequently asked questions

Chatgpt 4o Latest has a larger context window: 128K tokens vs 100K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

Powered by Mem0

Use a smaller model.
Get better results.

Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.

Example: a multi-turn chat session

Without Mem0~128K tokens sent
Full history
Repeated info
Old context
With Mem0~20K tokens sent
Key memories
Current turn

80% less to send — works with any model