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Nano Banana Pro (Gemini 3 Pro Image) vs Llama 3.3 70B Instruct (free)

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

Nano Banana Pro (Gemini 3 Pro Image)

Image inputTool calling

Context window

66K

65,536 tokens · ~49K words

Model page
Meta

Model

Llama 3.3 70B Instruct (free)

Tool calling

Context window

66K

65,536 tokens · ~49K 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.

Nano Banana Pro (Gemini 3 Pro Image)66K
Llama 3.3 70B Instruct (free)66K

Same context window size for both models.

Nano Banana Pro (Gemini 3 Pro Image) and Llama 3.3 70B Instruct (free) have identical context windows (65K tokens).

Full specs

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

SpecNano Banana Pro (Gemini 3 Pro Image)Llama 3.3 70B Instruct (free)
Context window65,536 tokens (65K)65,536 tokens (65K)
Max output tokens32,768 tokens (32K)N/A
Speed tierFastDeep
VisionYesNo
Function callingYesYes
Extended thinkingYesNo
Prompt cachingYesNo
Batch APINoNo
Release dateJun 2026Dec 2024

Frequently asked questions

Llama 3.3 70B Instruct (free) has a larger context window: 65K tokens vs 65K. 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