Context Window

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Autoglm Phone 9b Multilingual vs Nano Banana 2 (Gemini 3.1 Flash Image)

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.

Z Ai

Model

Autoglm Phone 9b Multilingual

Image input

Context window

66K

65,536 tokens · ~49K words

Model page
Google

Model

Nano Banana 2 (Gemini 3.1 Flash Image)

Image input

Context window

131K

131,072 tokens · ~98K 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.

Autoglm Phone 9b Multilingual66K
Nano Banana 2 (Gemini 3.1 Flash Image)131K

Nano Banana 2 (Gemini 3.1 Flash Image) has about 2× the context window of the other in this pair.

Token calculator →Memory savings →

Nano Banana 2 (Gemini 3.1 Flash Image) has 100% more context capacity (131K vs 65K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Nano Banana 2 (Gemini 3.1 Flash Image). Its 131K context fits entire documents without chunking (vs 65K).

Full specs

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

SpecAutoglm Phone 9b MultilingualNano Banana 2 (Gemini 3.1 Flash Image)
Context window65,536 tokens (65K)131,072 tokens (131K)
Max output tokens65,536 tokens (65K)65,536 tokens (65K)
Speed tierBalancedFast
VisionYesYes
Function callingNoNo
Extended thinkingNoYes
Prompt cachingNoNo
Batch APINoNo
Release dateN/AJun 2026

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.

ProviderAutoglm Phone 9b Multilingual inAutoglm Phone 9b Multilingual outNano Banana 2 (Gemini 3.1 Flash Image) inNano Banana 2 (Gemini 3.1 Flash Image) out
Novita$0.035/M$0.138/M——

Frequently asked questions

Nano Banana 2 (Gemini 3.1 Flash Image) has a larger context window: 131K 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.
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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.

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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