Qwen3.7 Max
$6.25
estimated usage cost
1,000 requests × (1,000 uncached input × $2.50 + 500 output × $7.50) / 1,000,000 = $6.25
base rates; no context pricing tiers are published.
Text generation / Qwen
Qwen3.7 Max
Qwen3.7 Max is a text generation model from Qwen, available through the Impossibl API. Its published context window is 1,048,576 tokens. The advertised input rate is $2.50 per million input tokens. The advertised output rate is $7.50 per million output tokens.
api id: qwen/qwen3.7-max
how much does qwen3.7 max cost?
published base api rates · usd per 1m tokens
- input
- $2.50
- output
- $7.50
- cache read
- $0.50
rates are published by the impossibl api. balance-purchase fees, taxes, tool charges, and workspace-specific pricing are separate.
specifications & capabilities
- creator
- Qwen
- model type
- Text generation
- context window
- 1.05m tokens
- maximum output
- not published in the catalog
- input types
- text
- output types
- text
- tool calling
- not verified in the catalog
unknown means the public catalog does not establish that fact. a model's documented capabilities can differ from what a particular api supports.
estimate your usage
estimate your api cost
estimate text token usage for your workload. all amounts are in usd.
estimates use published impossibl api usage rates. configured billing adjustments, funding fees, taxes, and custom workspace rates are excluded and may change the final amount.
image and audio usage, cache creation, and additional tool charges are excluded. reasoning tokens count as billable output, even when they are not visible in the response.
compare more Text generation models
- Qwen3.6 Flash$0.25 input / 1m tokenscompare →
- Qwen3.7 Plus$0.40 input / 1m tokenscompare →
- Qwen3.8 2.4T A95B$1.20 input / 1m tokenscompare →
- Qwen3.8 27B$0.50 input / 1m tokenscompare →
independent benchmarks
Results from Artificial Analysis. Each configuration is listed separately. These evaluations describe the tested model configuration; performance and costs can differ on Impossibl. Last checked 2026-09-11.
Qwen3.7 Max
| Benchmark | Score |
|---|---|
| Intelligence Index | 29.87 |
| Omniscience Index | 13.48 |
| GPQA | 92.32% |
| Humanity’s Last Exam | 40.50% |
| SciCode | 49.54% |
| CritPt | 13.43% |
| Terminal-Bench v2.1 | 74.53% |
| Terminal-Bench v4.0 | 1.52% |
| Terminal-Bench Hard | 50.76% |
| AA-LCR | 79.00% |
| Harvey LAB | 83.43% |
| GDPval Elo | 1189.86 |
| GDP.pdf All-pass | 8.60% |
| AutomationBench Partial | 22.98% |
| AnalystAgent | 18.75% |
| IFBench | 80.54% |
| Tau2 | 94.74% |
| Tau Banking | 11.75% |
| ITBench | 42.47% |
| coding index (API) | 66 |
| agentic index (API) | 23.9 |
| intelligence index (API) | 29.9 |
Unmeasured scores are omitted. API values retain their source units.
view source ↗frequently asked questions
What is Qwen3.7 Max?
Qwen3.7 Max is a text-generation model from Qwen, available through the Impossibl API.
How much does Qwen3.7 Max cost?
Qwen3.7 Max costs $2.50 per million input tokens and $7.50 per million output tokens through the Impossibl API. Cache reads cost $0.50 per million tokens. All rates are in USD.
What is the context length of Qwen3.7 Max?
Qwen3.7 Max has a 1,048,576-token context window through the Impossibl API.
What inputs and outputs does Qwen3.7 Max support?
Qwen3.7 Max accepts text as input. Qwen3.7 Max returns text.
How do I use Qwen3.7 Max through an API?
Qwen3.7 Max is available through the Impossibl API. Use qwen/qwen3.7-max as the model identifier with /v1/chat/completions. The quickstart explains how to create an API key and send your first request.
When was Qwen3.7 Max released?
Qwen released Qwen3.7 Max on May 21, 2026.
sources & coverage
this page describes Qwen3.7 Max as listed by the impossibl public api. prices and availability come from that catalog, refreshed here every five minutes. this is an impossibl offering, not a comparison of independent hosting-provider quotes.
model descriptions and release dates, where available, use the creator sources linked in the faq. api prices and limits use the impossibl catalog. benchmark results, where available, are credited to Artificial Analysis in the benchmarks section. report a correction →