Context Window

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Meta Llama 3 2 1b vs Minimax M2 5

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 Llama 3 2 1b

Context window

16K

16,384 tokens · ~12K words

Model page
Minimax

Model

Minimax M2 5

Tool calling

Context window

1M

1,000,000 tokens · ~750K 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 Llama 3 2 1b16K
Minimax M2 51M

Minimax M2 5 has about 61× the context window of the other in this pair.

Token calculator →Memory savings →

Minimax M2 5 has 6003% more context capacity (1000K vs 16K tokens). Meta Llama 3 2 1b is 86% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Minimax M2 5. Its 1000K context fits entire documents without chunking (vs 16K).

  • RAG / high-volume retrieval

    Use Meta Llama 3 2 1b. Input tokens are 86% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Meta Llama 3 2 1b. Its 16K 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 Llama 3 2 1bMinimax M2 5
Context window16,384 tokens (16K)1,000,000 tokens (1000K)
Max output tokens16,384 tokens (16K)8,192 tokens (8K)
Speed tierFastFast
VisionNoNo
Function callingNoYes
Extended thinkingNoYes
Prompt cachingNoYes
Batch APINoNo
Release dateN/AN/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.

ProviderMeta Llama 3 2 1b inMeta Llama 3 2 1b outMinimax M2 5 inMinimax M2 5 out
Baseten——$0.300/M$1.20/M
Minimax——$0.300/M$1.20/M
Openrouter——$0.300/M$1.10/M
Sambanova$0.040/M$0.080/M——

Frequently asked questions

Minimax M2 5 has a larger context window: 1000K tokens vs 16K. 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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Example: a multi-turn chat session

Without Mem0~128K tokens sent
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