Context Window

Compare

Hy3 preview (free) vs Meta Llama3 2 11b Instruct

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.

Tencent

Model

Hy3 preview (free)

Tool calling

Context window

262K

262,144 tokens · ~197K words

Model page
Meta

Model

Meta Llama3 2 11b Instruct

Image inputTool 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.

Hy3 preview (free)262K
Meta Llama3 2 11b Instruct128K

Hy3 preview (free) has about 2× the context window of the other in this pair.

Token calculator →Memory savings →

Hy3 preview (free) has 104% more context capacity (262K vs 128K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Hy3 preview (free). Its 262K context fits entire documents without chunking (vs 128K).

  • Long output (reports, code files)

    Use Hy3 preview (free). Its 262K 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.

SpecHy3 preview (free)Meta Llama3 2 11b Instruct
Context window262,144 tokens (262K)128,000 tokens (128K)
Max output tokens262,144 tokens (262K)4,096 tokens (4K)
Speed tierBalancedFast
VisionNoYes
Function callingYesYes
Extended thinkingYesNo
Prompt cachingNoNo
Batch APINoNo
Release dateApr 2026N/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.

ProviderHy3 preview (free) inHy3 preview (free) outMeta Llama3 2 11b Instruct inMeta Llama3 2 11b Instruct out
Aws Bedrock——$0.350/M$0.350/M

Frequently asked questions

Hy3 preview (free) has a larger context window: 262K 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