Context Window

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Amazon Titan Text Express vs Starcoder2 15b

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
Bigcode

Model

Starcoder2 15b

Context window

16K

16,384 tokens · ~12K 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
Starcoder2 15b16K

Amazon Titan Text Express has about 2.6× the context window of the other in this pair.

Token calculator →Memory savings →

Amazon Titan Text Express has 156% more context capacity (42K vs 16K tokens). Starcoder2 15b is 84% 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 16K).

  • RAG / high-volume retrieval

    Use Starcoder2 15b. Input tokens are 84% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Starcoder2 15b. 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.

SpecAmazon Titan Text ExpressStarcoder2 15b
Context window42,000 tokens (42K)16,384 tokens (16K)
Max output tokens8,000 tokens (8K)16,384 tokens (16K)
Speed tierBalancedBalanced
VisionNoNo
Function callingNoNo
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 Express inAmazon Titan Text Express outStarcoder2 15b inStarcoder2 15b out
Aws Bedrock$1.30/M$1.70/M——
Fireworks——$0.200/M$0.200/M

Frequently asked questions

Amazon Titan Text Express has a larger context window: 42K 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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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