AllocateInkling FP4 vs GLM 5.2
On provider list prices, Inkling FP4 costs $1 per million input tokens against $1.40 for GLM 5.2: 1.4x apart. Output is $4.05 against $4.40 (1.1x).
Inkling FP4G GLM 5.2Specifications and provider list prices from the Allocate catalog, checked 2026-07-21.
What the numbers say
Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $2,618 a month on Inkling FP4 and $3,220 on GLM 5.2 at list: a gap of $602.50, or 1.2x.
Inkling FP4 reads 512K tokens per request against 256K for GLM 5.2, 2.0x the window. That decides which one can take whole documents without splitting them.
Choose Inkling FP4 for
- The lower list price ($1 in / $4.05 out per M tokens)
- The longer context window (512K vs 256K 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, Inkling FP4 or GLM 5.2?
Inkling FP4, on this workload shape. At list prices it is $1/$4.05 per million tokens in and out against $1.40/$4.40 for GLM 5.2. Billed on Allocate: $1.07/$4.33 against $1.50/$4.71.
Which has the bigger context window?
Inkling FP4: 524,288 tokens (512K) against 262,144 (256K) for GLM 5.2.
Can I fine-tune Inkling FP4 or GLM 5.2?
Both publish open weights (Inkling FP4: 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.