Compare
Minimax M2 1 Lightning vs Openai Gpt 4o
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 M2 1 Lightning
Context window
1M
1,000,000 tokens · ~750K 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 M2 1 Lightning has about 7.8× the context window of the other in this pair.
Minimax M2 1 Lightning has 681% more context capacity (1000K vs 128K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Minimax M2 1 Lightning. Its 1000K context fits entire documents without chunking (vs 128K).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Minimax M2 1 Lightning | Openai Gpt 4o |
|---|---|---|
| Context window | 1,000,000 tokens (1000K) | 128,000 tokens (128K) |
| Max output tokens | 8,192 tokens (8K) | N/A |
| Speed tier | Fast | Balanced |
| Vision | No | No |
| Function calling | Yes | No |
| Extended thinking | Yes | No |
| Prompt caching | Yes | No |
| Batch API | No | Yes |
| Release date | N/A | 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 M2 1 Lightning in | Minimax M2 1 Lightning out | Openai Gpt 4o in | Openai Gpt 4o out |
|---|---|---|---|---|
| Gradient | — | — | — | — |
| Minimax | $0.300/M | $2.40/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