Context Window

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Gemini 3 8 Flash Cyber vs Hy3

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 3 8 Flash Cyber

Image input

Context window

1.0M

1,048,576 tokens · ~786K words

Model page
Tencent

Model

Hy3

Tool calling

Context window

262K

262,144 tokens · ~197K 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 3 8 Flash Cyber1.0M
Hy3262K

Gemini 3 8 Flash Cyber has about 4× the context window of the other in this pair.

Token calculator →Memory savings →

Gemini 3 8 Flash Cyber has 300% more context capacity (1048K vs 262K tokens). Hy3 is 91% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Gemini 3 8 Flash Cyber. Its 1048K context fits entire documents without chunking (vs 262K).

  • RAG / high-volume retrieval

    Use Hy3. Input tokens are 91% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Hy3. Its 131K 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 3 8 Flash CyberHy3
Context window1,048,576 tokens (1048K)262,144 tokens (262K)
Max output tokens65,536 tokens (65K)131,072 tokens (131K)
Speed tierFastBalanced
VisionYesNo
Function callingNoYes
Extended thinkingYesYes
Prompt cachingYesYes
Batch APINoNo
Release dateN/AJul 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.

ProviderGemini 3 8 Flash Cyber inGemini 3 8 Flash Cyber outHy3 inHy3 out
Deepinfra——$0.140/M$0.580/M
Google Vertex$1.50/M$7.50/M——
Novita——$0.140/M$0.580/M
Openrouter——$0.132/M$0.528/M

Frequently asked questions

Gemini 3 8 Flash Cyber has a larger context window: 1048K tokens vs 262K. 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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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