AllocateQwen 3.5 vs GLM 5.2
On provider list prices, Qwen 3.5 costs $0.60 per million input tokens against $1.40 for GLM 5.2: 2.3x apart. Output is $3.60 against $4.40 (1.2x). On Allocate both bill at list plus the 7% transaction fee.
Qwen 3.5G 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 $1,980 a month on Qwen 3.5 and $3,220 on GLM 5.2 at list: a gap of $1,240, or 1.6x.
Choose Qwen 3.5 for
- Multilingual support agents
- Translation-adjacent workflows
- Fine-tuning under 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, Qwen 3.5 or GLM 5.2?
Qwen 3.5, on this workload shape. At list prices it is $0.60/$3.60 per million tokens in and out against $1.40/$4.40 for GLM 5.2. Billed on Allocate: $0.64/$3.85 against $1.50/$4.71, list plus 7%.
Which has the bigger context window?
They match: both read 262,144 tokens (256K) per request.
Can I fine-tune Qwen 3.5 or GLM 5.2?
Both publish open weights (Qwen 3.5: 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.