AllocateGemini 3.1 Pro vs OpenAI GPT-OSS 120B
On provider list prices, OpenAI GPT-OSS 120B costs $0.15 per million input tokens against $2 for Gemini 3.1 Pro: 13.3x apart. Output is $0.60 against $12 (20.0x). On Allocate both bill at list plus the 7% transaction fee.
Gemini 3.1 Pro
OpenAI GPT-OSS 120BSpecifications 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 $390 a month on OpenAI GPT-OSS 120B and $6,600 on Gemini 3.1 Pro at list: a gap of $6,210, or 16.9x.
Gemini 3.1 Pro reads 1M tokens per request against 128K for OpenAI GPT-OSS 120B, 7.6x the window. That decides which one can take whole documents without splitting them.
Choose Gemini 3.1 Pro for
- Judgment-heavy workflows
- Long-context analysis
- Escalation tier above Flash
Choose OpenAI GPT-OSS 120B for
- The lower list price ($0.15 in / $0.60 out per M tokens)
- Open weights you can fine-tune and own
Common questions
Which is cheaper, Gemini 3.1 Pro or OpenAI GPT-OSS 120B?
OpenAI GPT-OSS 120B, on this workload shape. At list prices it is $0.15/$0.60 per million tokens in and out against $2/$12 for Gemini 3.1 Pro. Billed on Allocate: $0.16/$0.64 against $2.14/$12.84, list plus 7%.
Which has the bigger context window?
Gemini 3.1 Pro: 1,000,000 tokens (1M) against 131,072 (128K) for OpenAI GPT-OSS 120B.
Can I fine-tune Gemini 3.1 Pro or OpenAI GPT-OSS 120B?
OpenAI GPT-OSS 120B publishes open weights (Custom license) and can be fine-tuned on your own data. Gemini 3.1 Pro 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.