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MiniMax M3 (batch) vs O3 Mini 2025 01 31
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
MiniMax M3 (batch)
Context window
524K
524,288 tokens · ~393K 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.
MiniMax M3 (batch) has about 2.6× the context window of the other in this pair.
MiniMax M3 (batch) has 162% more context capacity (524K vs 200K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use MiniMax M3 (batch). Its 524K context fits entire documents without chunking (vs 200K).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | MiniMax M3 (batch) | O3 Mini 2025 01 31 |
|---|---|---|
| Context window | 524,288 tokens (524K) | 200,000 tokens (200K) |
| Max output tokens | N/A | 100,000 tokens (100K) |
| Speed tier | Fast | Fast |
| Vision | Yes | No |
| Function calling | Yes | No |
| Extended thinking | Yes | Yes |
| Prompt caching | Yes | Yes |
| Batch API | No | Yes |
| Release date | May 2026 | 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 | MiniMax M3 (batch) in | MiniMax M3 (batch) out | O3 Mini 2025 01 31 in | O3 Mini 2025 01 31 out |
|---|---|---|---|---|
| Azure | — | — | $1.21/M | $4.84/M |
| Openai | — | — | $1.10/M | $4.40/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