Compare
o1 (batch) vs o3 Pro
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
o1 (batch)
Context window
200K
200,000 tokens · ~150K 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.
Same context window size for both models.
o1 (batch) and o3 Pro have identical context windows (200K tokens).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | o1 (batch) | o3 Pro |
|---|---|---|
| Context window | 200,000 tokens (200K) | 200,000 tokens (200K) |
| Max output tokens | 100,000 tokens (100K) | 100,000 tokens (100K) |
| Speed tier | Deep | Deep |
| Vision | Yes | Yes |
| Function calling | Yes | Yes |
| Extended thinking | Yes | Yes |
| Prompt caching | Yes | No |
| Batch API | Yes | Yes |
| Release date | Dec 2024 | Jun 2025 |
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