Compare
Amazon Titan Text Express vs Grok 4 20 Non Reasoning
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.
Model
Grok 4 20 Non Reasoning
Context window
2M
2,000,000 tokens · ~1.5M words
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.
Grok 4 20 Non Reasoning has about 47.6× the context window of the other in this pair.
Grok 4 20 Non Reasoning has 4661% more context capacity (2000K vs 42K tokens). Amazon Titan Text Express is 35% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Grok 4 20 Non Reasoning. Its 2000K context fits entire documents without chunking (vs 42K).
RAG / high-volume retrieval
Use Amazon Titan Text Express. Input tokens are 35% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Grok 4 20 Non Reasoning. Its 2000K 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 | Grok 4 20 Non Reasoning |
|---|---|---|
| Context window | 42,000 tokens (42K) | 2,000,000 tokens (2000K) |
| Max output tokens | 8,000 tokens (8K) | 2,000,000 tokens (2000K) |
| Speed tier | Balanced | Deep |
| Vision | No | Yes |
| Function calling | No | Yes |
| Extended thinking | No | No |
| Prompt caching | No | Yes |
| Batch API | No | No |
| Release date | N/A | N/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.
| Provider | Amazon Titan Text Express in | Amazon Titan Text Express out | Grok 4 20 Non Reasoning in | Grok 4 20 Non Reasoning out |
|---|---|---|---|---|
| Aws Bedrock | $1.30/M | $1.70/M | — | — |
| Google Vertex | — | — | $2.00/M | $6.00/M |
Frequently asked questions
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.
Example: a multi-turn chat session
80% less to send — works with any model