AllocateOpenAI GPT-OSS 20B vs GLM 5.2
On provider list prices, OpenAI GPT-OSS 20B costs $0.05 per million input tokens against $1.40 for GLM 5.2: 28.0x apart. Output is $0.20 against $4.40 (22.0x). On Allocate both bill at list plus the 7% transaction fee.
OpenAI GPT-OSS 20BG GLM 5.2Specifications 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 $3,220 on GLM 5.2 at list: a gap of $3,090, or 24.8x.
GLM 5.2 reads 256K tokens per request against 128K for OpenAI GPT-OSS 20B, 2.0x 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)
- Fine-tuning under a permissive license (Apache 2.0)
Choose GLM 5.2 for
- Agents on open weights
- Code and structured outputs
- Fine-tuning toward an owned model
Common questions
Which is cheaper, OpenAI GPT-OSS 20B or GLM 5.2?
OpenAI GPT-OSS 20B, on this workload shape. At list prices it is $0.05/$0.20 per million tokens in and out against $1.40/$4.40 for GLM 5.2. Billed on Allocate: $0.053/$0.21 against $1.50/$4.71, list plus 7%.
Which has the bigger context window?
GLM 5.2: 262,144 tokens (256K) against 131,072 (128K) for OpenAI GPT-OSS 20B.
Can I fine-tune OpenAI GPT-OSS 20B or GLM 5.2?
Both publish open weights (OpenAI GPT-OSS 20B: Apache 2.0; GLM 5.2: Not listed), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.
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.