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Coder Large 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.
Model
Nano Banana 2 (Gemini 3.1 Flash Image)
Context window
131K
131,072 tokens · ~98K words
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) has about 4× the context window of the other in this pair.
Nano Banana 2 (Gemini 3.1 Flash Image) has 300% more context capacity (131K vs 32K 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 32K).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Coder Large | Nano Banana 2 (Gemini 3.1 Flash Image) |
|---|---|---|
| Context window | 32,768 tokens (32K) | 131,072 tokens (131K) |
| Max output tokens | N/A | 65,536 tokens (65K) |
| Speed tier | Deep | Fast |
| Vision | No | Yes |
| Function calling | No | No |
| Extended thinking | No | Yes |
| Prompt caching | No | No |
| Batch API | No | No |
| Release date | May 2025 | Jun 2026 |
Frequently asked questions
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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.
Example: a multi-turn chat session
80% less to send — works with any model