Context Window

Compare

Amazon Titan Text Lite vs o1

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
Openai

Model

o1

Image inputTool calling

Context window

200K

200,000 tokens · ~150K 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
o1200K

o1 has about 4.8× the context window of the other in this pair.

Token calculator →Memory savings →

o1 has 376% more context capacity (200K vs 42K tokens). Amazon Titan Text Lite is 98% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use o1. Its 200K context fits entire documents without chunking (vs 42K).

  • RAG / high-volume retrieval

    Use Amazon Titan Text Lite. Input tokens are 98% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use o1. Its 100K 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 Liteo1
Context window42,000 tokens (42K)200,000 tokens (200K)
Max output tokens4,000 tokens (4K)100,000 tokens (100K)
Speed tierBalancedDeep
VisionNoYes
Function callingNoYes
Extended thinkingNoYes
Prompt cachingNoYes
Batch APINoYes
Release dateN/ADec 2024

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 outo1 ino1 out
Aws Bedrock$0.300/M$0.400/M——
Azure——$15.00/M$60.00/M
Openai——$15.00/M$60.00/M
Openrouter——$15.00/M$60.00/M
Replicate——$15.00/M$60.00/M

Frequently asked questions

o1 has a larger context window: 200K tokens vs 42K. 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.

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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