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Amazon Titan Text Express vs Virtuoso Large
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.
Virtuoso Large has about 3.1× the context window of the other in this pair.
Virtuoso Large has 212% more context capacity (131K vs 42K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Virtuoso Large. Its 131K context fits entire documents without chunking (vs 42K).
Long output (reports, code files)
Use Virtuoso Large. Its 64K 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.
| Spec | Amazon Titan Text Express | Virtuoso Large |
|---|---|---|
| Context window | 42,000 tokens (42K) | 131,072 tokens (131K) |
| Max output tokens | 8,000 tokens (8K) | 64,000 tokens (64K) |
| Speed tier | Balanced | Deep |
| Vision | No | No |
| Function calling | No | Yes |
| Extended thinking | No | No |
| Prompt caching | No | No |
| Batch API | No | No |
| Release date | N/A | May 2025 |
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 | Virtuoso Large in | Virtuoso Large 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
80% less to send — works with any model