Context Window

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Nano Banana 2 (Gemini 3.1 Flash Image) vs Gpt Oss 20b Mxfp4 Gguf

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 2 (Gemini 3.1 Flash Image)

Image input

Context window

131K

131,072 tokens · ~98K words

Model page
Openai

Model

Gpt Oss 20b Mxfp4 Gguf

Tool calling

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.

Nano Banana 2 (Gemini 3.1 Flash Image)131K
Gpt Oss 20b Mxfp4 Gguf131K

Same context window size for both models.

Token calculator →Memory savings →

Nano Banana 2 (Gemini 3.1 Flash Image) and Gpt Oss 20b Mxfp4 Gguf have identical context windows (131K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long output (reports, code files)

    Use Nano Banana 2 (Gemini 3.1 Flash Image). Its 65K 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.

SpecNano Banana 2 (Gemini 3.1 Flash Image)Gpt Oss 20b Mxfp4 Gguf
Context window131,072 tokens (131K)131,072 tokens (131K)
Max output tokens65,536 tokens (65K)32,768 tokens (32K)
Speed tierFastBalanced
VisionYesNo
Function callingNoYes
Extended thinkingYesNo
Prompt cachingNoNo
Batch APINoNo
Release dateJun 2026N/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.

ProviderNano Banana 2 (Gemini 3.1 Flash Image) inNano Banana 2 (Gemini 3.1 Flash Image) outGpt Oss 20b Mxfp4 Gguf inGpt Oss 20b Mxfp4 Gguf out
Lemonade————

Frequently asked questions

Gpt Oss 20b Mxfp4 Gguf has a larger context window: 131K tokens vs 131K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

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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.

Calculate your savingsLearn about Mem0

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