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R1 vs Minimax M2 7 Highspeed
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 7 Highspeed
Context window
205K
204,800 tokens · ~154K 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 7 Highspeed has about 1.6× the context window of the other in this pair.
Minimax M2 7 Highspeed has 60% more context capacity (204K vs 128K tokens). R1 is 8% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Minimax M2 7 Highspeed. Its 204K context fits entire documents without chunking (vs 128K).
RAG / high-volume retrieval
Use R1. Input tokens are 8% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Minimax M2 7 Highspeed. Its 131K 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 | R1 | Minimax M2 7 Highspeed |
|---|---|---|
| Context window | 128,000 tokens (128K) | 204,800 tokens (204K) |
| Max output tokens | 8,192 tokens (8K) | 131,072 tokens (131K) |
| Speed tier | Deep | Fast |
| Vision | No | No |
| Function calling | Yes | Yes |
| Extended thinking | Yes | Yes |
| Prompt caching | Yes | Yes |
| Batch API | No | No |
| Release date | Jan 2025 | 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 | R1 in | R1 out | Minimax M2 7 Highspeed in | Minimax M2 7 Highspeed out |
|---|---|---|---|---|
| Aws Bedrock | $1.35/M | $5.40/M | — | — |
| Azure | $1.35/M | $5.40/M | — | — |
| Deepinfra | $0.700/M | $2.40/M | — | — |
| Deepseek | $0.550/M | $2.19/M | — | — |
| Fireworks | $3.00/M | $8.00/M | — | — |
| Hyperbolic | $0.400/M | $0.400/M | — | — |
| Nebius | $0.800/M | $2.40/M | — | — |
| Novita | $0.700/M | $2.50/M | $0.600/M | $2.40/M |
| Openrouter | $0.700/M | $2.50/M | — | — |
| Replicate | $3.75/M | $10.00/M | — | — |
| Sambanova | $5.00/M | $7.00/M | — | — |
| Snowflake | $1.35/M | $5.40/M | — | — |
| Together Ai | $3.00/M | $7.00/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