AllocateMiniMax M3 vs OpenAI GPT-OSS 20B
On provider list prices, OpenAI GPT-OSS 20B costs $0.05 per million input tokens against $0.30 for MiniMax M3: 6.0x apart. Output is $0.20 against $1.20 (6.0x). On Allocate both bill at list plus the 7% transaction fee.
OpenAI GPT-OSS 20BSpecifications 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 $780 on MiniMax M3 at list: a gap of $650, or 6.0x.
MiniMax M3 reads 512K tokens per request against 128K for OpenAI GPT-OSS 20B, 4.0x the window. That decides which one can take whole documents without splitting them.
Choose MiniMax M3 for
- The longer context window (512K vs 128K tokens)
- Published cached-input pricing ($0.06 per M tokens)
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)
Common questions
Which is cheaper, MiniMax M3 or OpenAI GPT-OSS 20B?
OpenAI GPT-OSS 20B, on this workload shape. At list prices it is $0.05/$0.20 per million tokens in and out against $0.30/$1.20 for MiniMax M3. Billed on Allocate: $0.053/$0.21 against $0.32/$1.28, list plus 7%.
Which has the bigger context window?
MiniMax M3: 524,288 tokens (512K) against 131,072 (128K) for OpenAI GPT-OSS 20B.
Can I fine-tune MiniMax M3 or OpenAI GPT-OSS 20B?
OpenAI GPT-OSS 20B publishes open weights (Apache 2.0) and can be fine-tuned on your own data. MiniMax M3 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.