Context Window

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Amazon Titan Text Express vs ReMM SLERP 13B

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 Express

Context window

42K

42,000 tokens · ~32K words

Model page
Undi95

Model

ReMM SLERP 13B

Context window

6K

6,144 tokens · ~5K 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 Express42K
ReMM SLERP 13B6K

Amazon Titan Text Express has about 6.8× the context window of the other in this pair.

Token calculator →Memory savings →

Amazon Titan Text Express has 583% more context capacity (42K vs 6K tokens). Amazon Titan Text Express is 30% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Amazon Titan Text Express. Its 42K context fits entire documents without chunking (vs 6K).

  • RAG / high-volume retrieval

    Use Amazon Titan Text Express. Input tokens are 30% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Amazon Titan Text Express. 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.

SpecAmazon Titan Text ExpressReMM SLERP 13B
Context window42,000 tokens (42K)6,144 tokens (6K)
Max output tokens8,000 tokens (8K)4,096 tokens (4K)
Speed tierBalancedFast
VisionNoNo
Function callingNoNo
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateN/AJul 2023

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 Express inAmazon Titan Text Express outReMM SLERP 13B inReMM SLERP 13B out
Aws Bedrock$1.30/M$1.70/M——
Openrouter——$1.88/M$1.88/M

Frequently asked questions

Amazon Titan Text Express has a larger context window: 42K tokens vs 6K. 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