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DeepSeek V3.1 vs MiniMax-01
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.
MiniMax-01 has about 6.1× the context window of the other in this pair.
MiniMax-01 has 510% more context capacity (1000K vs 163K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use MiniMax-01. Its 1000K context fits entire documents without chunking (vs 163K).
Long output (reports, code files)
Use MiniMax-01. Its 1000K 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 | DeepSeek V3.1 | MiniMax-01 |
|---|---|---|
| Context window | 163,840 tokens (163K) | 1,000,192 tokens (1000K) |
| Max output tokens | 163,840 tokens (163K) | 1,000,192 tokens (1000K) |
| Speed tier | Balanced | Fast |
| Vision | No | Yes |
| Function calling | Yes | No |
| Extended thinking | Yes | No |
| Prompt caching | Yes | No |
| Batch API | No | No |
| Release date | Aug 2025 | 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 | DeepSeek V3.1 in | DeepSeek V3.1 out | MiniMax-01 in | MiniMax-01 out |
|---|---|---|---|---|
| Openrouter | $0.200/M | $0.800/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
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