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Amazon Titan Text Express vs LFM2-24B-A2B
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.
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 Express has about 1.3× the context window of the other in this pair.
Amazon Titan Text Express has 28% more context capacity (42K vs 32K tokens).
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 32K).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Amazon Titan Text Express | LFM2-24B-A2B |
|---|---|---|
| Context window | 42,000 tokens (42K) | 32,768 tokens (32K) |
| Max output tokens | 8,000 tokens (8K) | N/A |
| Speed tier | Balanced | Balanced |
| Vision | No | No |
| Function calling | No | No |
| Extended thinking | No | No |
| Prompt caching | No | No |
| Batch API | No | No |
| Release date | N/A | Feb 2026 |
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.
| Provider | Amazon Titan Text Express in | Amazon Titan Text Express out | LFM2-24B-A2B in | LFM2-24B-A2B out |
|---|---|---|---|---|
| Aws Bedrock | $1.30/M | $1.70/M | — | — |
Frequently asked questions
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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.
Example: a multi-turn chat session
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