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R1 vs Qwen-Max
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.
R1 has about 4.2× the context window of the other in this pair.
R1 has 316% more context capacity (128K vs 30K tokens). R1 is 65% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use R1. Its 128K context fits entire documents without chunking (vs 30K).
RAG / high-volume retrieval
Use R1. Input tokens are 65% cheaper — critical when sending large retrieved contexts.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | R1 | Qwen-Max |
|---|---|---|
| Context window | 128,000 tokens (128K) | 30,720 tokens (30K) |
| Max output tokens | 8,192 tokens (8K) | 8,192 tokens (8K) |
| Speed tier | Deep | Balanced |
| Vision | No | No |
| Function calling | Yes | Yes |
| Extended thinking | Yes | Yes |
| Prompt caching | No | Yes |
| Batch API | No | No |
| Release date | Jan 2025 | Feb 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 | R1 in | R1 out | Qwen-Max in | Qwen-Max out |
|---|---|---|---|---|
| Alibaba Cloud | — | — | $1.60/M | $6.40/M |
| 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 | — | — |
| Openrouter | $0.550/M | $2.19/M | — | — |
| Replicate | $3.75/M | $10.00/M | — | — |
| Sambanova | $5.00/M | $7.00/M | — | — |
| Snowflake | — | — | — | — |
| Together Ai | $3.00/M | $7.00/M | — | — |
Frequently asked questions
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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