Compare

Gpt 5 2 Chat Latest vs o3 Deep Research

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.

Openai

Model

Gpt 5 2 Chat Latest

Image inputTool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Openai

Model

o3 Deep Research

Image inputTool calling

Context window

200K

200,000 tokens · ~150K 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.

Gpt 5 2 Chat Latest128K
o3 Deep Research200K

o3 Deep Research has about 1.6× the context window of the other in this pair.

o3 Deep Research has 56% more context capacity (200K vs 128K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use o3 Deep Research. Its 200K context fits entire documents without chunking (vs 128K).

  • Long output (reports, code files)

    Use o3 Deep Research. Its 100K 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.

SpecGpt 5 2 Chat Latesto3 Deep Research
Context window128,000 tokens (128K)200,000 tokens (200K)
Max output tokens16,384 tokens (16K)100,000 tokens (100K)
Speed tierBalancedDeep
VisionYesYes
Function callingYesYes
Extended thinkingYesYes
Prompt cachingYesYes
Batch APINoYes
Release dateN/AOct 2025

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.

ProviderGpt 5 2 Chat Latest inGpt 5 2 Chat Latest outo3 Deep Research ino3 Deep Research out
Openai$1.75/M$14.00/M

Frequently asked questions

o3 Deep Research has a larger context window: 200K tokens vs 128K. 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