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O3 2025 04 16 vs o3 Mini (batch)
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
O3 2025 04 16
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.
O3 2025 04 16 and o3 Mini (batch) have identical context windows (200K tokens).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | O3 2025 04 16 | o3 Mini (batch) |
|---|---|---|
| Context window | 200,000 tokens (200K) | 200,000 tokens (200K) |
| Max output tokens | 100,000 tokens (100K) | 100,000 tokens (100K) |
| Speed tier | Deep | Fast |
| Vision | Yes | No |
| Function calling | Yes | Yes |
| Extended thinking | Yes | Yes |
| Prompt caching | Yes | Yes |
| Batch API | Yes | Yes |
| 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 | O3 2025 04 16 in | O3 2025 04 16 out | o3 Mini (batch) in | o3 Mini (batch) out |
|---|---|---|---|---|
| Azure | $2.00/M | $8.00/M | — | — |
| Openai | $2.00/M | $8.00/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