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Qwen-Max vs Qwen Mt Plus
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.
Qwen-Max has about 1.9× the context window of the other in this pair.
Qwen-Max has 87% more context capacity (30K vs 16K tokens). Qwen Mt Plus is 84% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Qwen-Max. Its 30K context fits entire documents without chunking (vs 16K).
RAG / high-volume retrieval
Use Qwen Mt Plus. Input tokens are 84% 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 | Qwen-Max | Qwen Mt Plus |
|---|---|---|
| Context window | 30,720 tokens (30K) | 16,384 tokens (16K) |
| Max output tokens | 8,192 tokens (8K) | 8,192 tokens (8K) |
| Speed tier | Balanced | Balanced |
| Vision | No | No |
| Function calling | Yes | No |
| Extended thinking | Yes | No |
| Prompt caching | Yes | No |
| Batch API | No | No |
| Release date | Feb 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 | Qwen-Max in | Qwen-Max out | Qwen Mt Plus in | Qwen Mt Plus out |
|---|---|---|---|---|
| Alibaba Cloud | $1.60/M | $6.40/M | — | — |
| Novita | — | — | $0.250/M | $0.750/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