Context Window

Compare

Lyria 3 Clip Preview vs Meta Llama3 1 70b 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.

Google

Model

Lyria 3 Clip Preview

Image input

Context window

131K

131,072 tokens · ~98K words

Model page
Meta

Model

Meta Llama3 1 70b Instruct

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.

Lyria 3 Clip Preview131K
Meta Llama3 1 70b Instruct128K

Lyria 3 Clip Preview has about 1× the context window of the other in this pair.

Token calculator →Memory savings →

Lyria 3 Clip Preview has 2% more context capacity (131K vs 128K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Lyria 3 Clip Preview. Its 131K context fits entire documents without chunking (vs 128K).

  • Long output (reports, code files)

    Use Lyria 3 Clip Preview. Its 8K 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.

SpecLyria 3 Clip PreviewMeta Llama3 1 70b Instruct
Context window131,072 tokens (131K)128,000 tokens (128K)
Max output tokens8,192 tokens (8K)2,048 tokens (2K)
Speed tierBalancedDeep
VisionYesNo
Function callingNoYes
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateMar 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.

ProviderLyria 3 Clip Preview inLyria 3 Clip Preview outMeta Llama3 1 70b Instruct inMeta Llama3 1 70b Instruct out
Aws Bedrock——$0.990/M$0.990/M
Google————

Frequently asked questions

Lyria 3 Clip Preview has a larger context window: 131K 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