Context Window

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Deepseek R1 0528 Qwen3 8b vs Gemini 2.5 Flash Lite

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.

Alibaba

Model

Deepseek R1 0528 Qwen3 8b

Context window

128K

128,000 tokens · ~96K words

Model page
Google

Model

Gemini 2.5 Flash Lite

Image inputTool calling

Context window

1.0M

1,048,576 tokens · ~786K 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.

Deepseek R1 0528 Qwen3 8b128K
Gemini 2.5 Flash Lite1.0M

Gemini 2.5 Flash Lite has about 8.2× the context window of the other in this pair.

Token calculator →Memory savings →

Gemini 2.5 Flash Lite has 719% more context capacity (1048K vs 128K tokens). Deepseek R1 0528 Qwen3 8b is 40% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Gemini 2.5 Flash Lite. Its 1048K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Deepseek R1 0528 Qwen3 8b. Input tokens are 40% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Gemini 2.5 Flash Lite. 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.

SpecDeepseek R1 0528 Qwen3 8bGemini 2.5 Flash Lite
Context window128,000 tokens (128K)1,048,576 tokens (1048K)
Max output tokens32,000 tokens (32K)65,535 tokens (65K)
Speed tierFastFast
VisionNoYes
Function callingNoYes
Extended thinkingYesYes
Prompt cachingNoYes
Batch APINoNo
Release dateN/AJul 2025

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.

ProviderDeepseek R1 0528 Qwen3 8b inDeepseek R1 0528 Qwen3 8b outGemini 2.5 Flash Lite inGemini 2.5 Flash Lite out
Google——$0.100/M$0.400/M
Google Vertex——$0.100/M$0.400/M
Novita$0.060/M$0.090/M——

Frequently asked questions

Gemini 2.5 Flash Lite 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.

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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