Context Window

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Amazon Titan Text Lite vs Granite 4 H Small

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.

Amazon

Model

Amazon Titan Text Lite

Context window

42K

42,000 tokens · ~32K words

Model page
Ibm

Model

Granite 4 H Small

Tool calling

Context window

20K

20,480 tokens · ~15K 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.

Amazon Titan Text Lite42K
Granite 4 H Small20K

Amazon Titan Text Lite has about 2.1× the context window of the other in this pair.

Token calculator →Memory savings →

Amazon Titan Text Lite has 105% more context capacity (42K vs 20K tokens). Granite 4 H Small is 80% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Amazon Titan Text Lite. Its 42K context fits entire documents without chunking (vs 20K).

  • RAG / high-volume retrieval

    Use Granite 4 H Small. Input tokens are 80% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Granite 4 H Small. Its 20K 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.

SpecAmazon Titan Text LiteGranite 4 H Small
Context window42,000 tokens (42K)20,480 tokens (20K)
Max output tokens4,000 tokens (4K)20,480 tokens (20K)
Speed tierBalancedBalanced
VisionNoNo
Function callingNoYes
Extended thinkingNoNo
Prompt cachingNoNo
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.

ProviderAmazon Titan Text Lite inAmazon Titan Text Lite outGranite 4 H Small inGranite 4 H Small out
Aws Bedrock$0.300/M$0.400/M——
Ibm Watsonx——$0.060/M$0.250/M

Frequently asked questions

Amazon Titan Text Lite has a larger context window: 42K tokens vs 20K. 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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Use a smaller model.
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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