Context Window

Compare

Gemma 3 4b It Gguf vs Qwen3.5-Flash

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

Gemma 3 4b It Gguf

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Alibaba

Model

Qwen3.5-Flash

Image inputTool calling

Context window

1M

1,000,000 tokens · ~750K 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.

Gemma 3 4b It Gguf128K
Qwen3.5-Flash1M

Qwen3.5-Flash has about 7.8× the context window of the other in this pair.

Token calculator →Memory savings →

Qwen3.5-Flash has 681% more context capacity (1000K vs 128K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Qwen3.5-Flash. Its 1000K context fits entire documents without chunking (vs 128K).

  • Long output (reports, code files)

    Use Qwen3.5-Flash. 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.

SpecGemma 3 4b It GgufQwen3.5-Flash
Context window128,000 tokens (128K)1,000,000 tokens (1000K)
Max output tokens8,192 tokens (8K)65,536 tokens (65K)
Speed tierBalancedFast
VisionNoYes
Function callingYesYes
Extended thinkingNoYes
Prompt cachingNoNo
Batch APINoNo
Release dateN/AFeb 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.

ProviderGemma 3 4b It Gguf inGemma 3 4b It Gguf outQwen3.5-Flash inQwen3.5-Flash out
Lemonade————
Openrouter——$0.100/M$0.400/M

Frequently asked questions

Qwen3.5-Flash has a larger context window: 1000K 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