Context Window

Compare

Meta Llama3 2 11b Instruct vs Seed-2.0-Mini

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.

Meta

Model

Meta Llama3 2 11b Instruct

Image inputTool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Bytedance

Model

Seed-2.0-Mini

Image inputTool 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.

Meta Llama3 2 11b Instruct128K
Seed-2.0-Mini262K

Seed-2.0-Mini has about 2× the context window of the other in this pair.

Token calculator →Memory savings →

Seed-2.0-Mini has 104% more context capacity (262K vs 128K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Seed-2.0-Mini. Its 262K context fits entire documents without chunking (vs 128K).

  • Long output (reports, code files)

    Use Seed-2.0-Mini. 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.

SpecMeta Llama3 2 11b InstructSeed-2.0-Mini
Context window128,000 tokens (128K)262,144 tokens (262K)
Max output tokens4,096 tokens (4K)131,072 tokens (131K)
Speed tierFastFast
VisionYesYes
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.

ProviderMeta Llama3 2 11b Instruct inMeta Llama3 2 11b Instruct outSeed-2.0-Mini inSeed-2.0-Mini out
Aws Bedrock$0.350/M$0.350/M——

Frequently asked questions

Seed-2.0-Mini 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