AllocateDeepSeek R1 0528 NVFP4 vs GLM 5.2
On provider list prices, GLM 5.2 costs $1.40 per million input tokens against $3 for DeepSeek R1 0528 NVFP4: 2.1x apart. Output is $4.40 against $7 (1.6x). On Allocate both bill at list plus the 7% transaction fee.
DeepSeek R1 0528 NVFP4G 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 $3,220 a month on GLM 5.2 and $6,050 on DeepSeek R1 0528 NVFP4 at list: a gap of $2,830, or 1.9x.
GLM 5.2 reads 256K tokens per request against 160K for DeepSeek R1 0528 NVFP4, 1.6x the window. That decides which one can take whole documents without splitting them.
Choose DeepSeek R1 0528 NVFP4 for
- Fine-tuning under a permissive license (MIT)
Choose GLM 5.2 for
- Agents on open weights
- Code and structured outputs
- Fine-tuning toward an owned model
Common questions
Which is cheaper, DeepSeek R1 0528 NVFP4 or GLM 5.2?
GLM 5.2, on this workload shape. At list prices it is $1.40/$4.40 per million tokens in and out against $3/$7 for DeepSeek R1 0528 NVFP4. Billed on Allocate: $1.50/$4.71 against $3.21/$7.49, list plus 7%.
Which has the bigger context window?
GLM 5.2: 262,144 tokens (256K) against 163,840 (160K) for DeepSeek R1 0528 NVFP4.
Can I fine-tune DeepSeek R1 0528 NVFP4 or GLM 5.2?
Both publish open weights (DeepSeek R1 0528 NVFP4: MIT; 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.