Context Window

Compare

Gemini Flash Lite Latest vs Gemma 3 4b It 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

Gemini Flash Lite Latest

Image inputTool calling

Context window

1.0M

1,048,576 tokens · ~786K words

Model page
Google

Model

Gemma 3 4b It Gguf

Tool calling

Context window

128K

128,000 tokens · ~96K 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.

Gemini Flash Lite Latest1.0M
Gemma 3 4b It Gguf128K

Gemini Flash Lite Latest has about 8.2× the context window of the other in this pair.

Token calculator →Memory savings →

Gemini Flash Lite Latest has 719% more context capacity (1048K vs 128K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Gemini Flash Lite Latest. Its 1048K context fits entire documents without chunking (vs 128K).

  • Long output (reports, code files)

    Use Gemini Flash Lite Latest. 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.

SpecGemini Flash Lite LatestGemma 3 4b It Gguf
Context window1,048,576 tokens (1048K)128,000 tokens (128K)
Max output tokens65,535 tokens (65K)8,192 tokens (8K)
Speed tierFastBalanced
VisionYesNo
Function callingYesYes
Extended thinkingYesNo
Prompt cachingYesNo
Batch APINoNo
Release dateN/AN/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.

ProviderGemini Flash Lite Latest inGemini Flash Lite Latest outGemma 3 4b It Gguf inGemma 3 4b It Gguf out
Google$0.100/M$0.400/M——
Lemonade————

Frequently asked questions

Gemini Flash Lite Latest has a larger context window: 1048K tokens vs 128K. 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.

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