Compare

Gemma 2 9B vs GPT-5.5 Pro

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.

Google

Model

Gemma 2 9B

Context window

8K

8,192 tokens · ~6K words

Model page
Openai

Model

GPT-5.5 Pro

Image inputTool calling

Context window

1.1M

1,050,000 tokens · ~788K 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.

Gemma 2 9B8K
GPT-5.5 Pro1.1M

GPT-5.5 Pro has about 128.2× the context window of the other in this pair.

GPT-5.5 Pro has 12717% more context capacity (1050K vs 8K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use GPT-5.5 Pro. Its 1050K context fits entire documents without chunking (vs 8K).

Full specs

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

SpecGemma 2 9BGPT-5.5 Pro
Context window8,192 tokens (8K)1,050,000 tokens (1050K)
Max output tokensN/A128,000 tokens (128K)
Speed tierBalancedBalanced
VisionNoYes
Function callingNoYes
Extended thinkingNoYes
Prompt cachingNoNo
Batch APINoNo
Release dateJun 2024Apr 2026

Frequently asked questions

GPT-5.5 Pro has a larger context window: 1050K tokens vs 8K. 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