Compare
O1 Preview vs Sonar
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.
Same context window size for both models.
O1 Preview and Sonar have identical context windows (128K tokens). Sonar is 93% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
RAG / high-volume retrieval
Use Sonar. Input tokens are 93% cheaper — critical when sending large retrieved contexts.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | O1 Preview | Sonar |
|---|---|---|
| Context window | 128,000 tokens (128K) | 128,000 tokens (128K) |
| Max output tokens | 32,768 tokens (32K) | N/A |
| Speed tier | Deep | Balanced |
| Vision | No | Yes |
| Function calling | Yes | No |
| Extended thinking | Yes | No |
| Prompt caching | Yes | No |
| Batch API | Yes | No |
| Release date | N/A | Jan 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 | O1 Preview in | O1 Preview out | Sonar in | Sonar out |
|---|---|---|---|---|
| Azure | $15.00/M | $60.00/M | — | — |
| Perplexity | — | — | $1.00/M | $1.00/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