AllocateOpenAI GPT-OSS 20B vs Qwen3.7 Max
On provider list prices, OpenAI GPT-OSS 20B costs $0.05 per million input tokens against $1.25 for Qwen3.7 Max: 25.0x apart. Output is $0.20 against $3.75 (18.8x). On Allocate both bill at list plus the 7% transaction fee.
OpenAI GPT-OSS 20B
Qwen3.7 MaxSpecifications and provider list prices from the Allocate catalog, checked 2026-07-08. Billed price is list plus the 7% transaction fee.
What the numbers say
Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $130 a month on OpenAI GPT-OSS 20B and $2,813 on Qwen3.7 Max at list: a gap of $2,683, or 21.6x.
Qwen3.7 Max reads 1M tokens per request against 128K for OpenAI GPT-OSS 20B, 7.6x the window. That decides which one can take whole documents without splitting them.
Choose OpenAI GPT-OSS 20B for
- The lower list price ($0.05 in / $0.20 out per M tokens)
- Open weights you can fine-tune and own
- Fine-tuning under a permissive license (Apache 2.0)
Choose Qwen3.7 Max for
- The longer context window (1M vs 128K tokens)
- Published cached-input pricing ($0.13 per M tokens)
Common questions
Which is cheaper, OpenAI GPT-OSS 20B or Qwen3.7 Max?
OpenAI GPT-OSS 20B, on this workload shape. At list prices it is $0.05/$0.20 per million tokens in and out against $1.25/$3.75 for Qwen3.7 Max. Billed on Allocate: $0.053/$0.21 against $1.34/$4.01, list plus 7%.
Which has the bigger context window?
Qwen3.7 Max: 1,000,000 tokens (1M) against 131,072 (128K) for OpenAI GPT-OSS 20B.
Can I fine-tune OpenAI GPT-OSS 20B or Qwen3.7 Max?
OpenAI GPT-OSS 20B publishes open weights (Apache 2.0) and can be fine-tuned on your own data. Qwen3.7 Max is a closed model served over API; its weights are not available.
Related comparisons
Run the numbers on your workload
Or don’t choose. On Allocate a route name is the contract: point yours at one model today, swap to the other tomorrow, and compare them on your live traffic with per-token metering.