Qwen3.7 Max API Pricing
Qwen3.7 Max costs $2.50 per 1M input tokens and $7.50 per 1M output tokens on Alibaba's API. Cached input is billed at $0.25 per 1M tokens. Prices are provider list prices in USD, refreshed as sources update; see the Qwen3.7 Max model profile for capability scores.
Price List
| Rate | Price (USD) | Notes |
|---|---|---|
| Input | $2.50 | per 1M tokens |
| Output | $7.50 | per 1M tokens |
| Cached input (read) | $0.25 | per 1M tokens |
| Cache write | $3.13 | per 1M tokens |
| Blended input + output | $10.00 | 1M in + 1M out at list price |
| Context window | 1M tokens |
What a Workload Costs
Computed straight from the list prices above — token counts are illustrative workload sizes, not measurements of Qwen3.7 Max.
| Workload | Cost | Tokens |
|---|---|---|
| Short chat turn | $0.00625 | 1K in / 500 out |
| Summarize a long document | $0.265 | 100K in / 2K out |
| Agentic coding session | $2.00 | 500K in / 100K out |
| 1M input + 1M output tokens | $10.00 | 1M in / 1M out |
Effective Cost
In AI IQ's scoring, Qwen3.7 Max's list price is adjusted by a token-usage multiplier of 1.799 (measured from real benchmark runs), giving an effective cost of $17.99 per 1M input + output tokens. That places it #93 of 117 models on the effective-cost ranking (lower is cheaper). Some models spend far more tokens than others on the same task, so effective cost compares what a unit of work really costs. Method details are on the methodology page; see all models on the cost charts and the falling cost of intelligence over time.
Cheaper Alternatives at Similar Capability
Models with a lower effective cost that score within a few IQ points of Qwen3.7 Max (IQ 118), or better.
| Model | Provider | IQ | Effective Cost / 1M |
|---|---|---|---|
| gpt-5.6-luna | OpenAI | 129 | $9.29 |
| gemini-3.1-pro | 127 | $9.47 | |
| kimi-k3 | Kimi | 123 | $15.40 |
| gemini-3.6-flash | 123 | $16.62 | |
| gemini-3.7-flash | 123 | $16.62 | |
| Muse Spark 1.2 | Meta | 122 | $4.19 |