AllocateInkling FP4 vs GLM 4.7 FP8
On provider list prices, GLM 4.7 FP8 costs $0.45 per million input tokens against $1 for Inkling FP4: 2.2x apart. Output is $2 against $4.05 (2.0x).
Inkling FP4G GLM 4.7 FP8Specifications 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 $1,240 a month on GLM 4.7 FP8 and $2,618 on Inkling FP4 at list: a gap of $1,378, or 2.1x.
Inkling FP4 reads 512K tokens per request against 198K for GLM 4.7 FP8, 2.6x the window. That decides which one can take whole documents without splitting them.
Choose Inkling FP4 for
- The longer context window (512K vs 198K tokens)
- Fine-tuning under a permissive license (Apache 2.0)
- Published cached-input pricing ($0.17 per M tokens)
Choose GLM 4.7 FP8 for
- The lower list price ($0.45 in / $2 out per M tokens)
- Fine-tuning under a permissive license (MIT)
Common questions
Which is cheaper, Inkling FP4 or GLM 4.7 FP8?
GLM 4.7 FP8, on this workload shape. At list prices it is $0.45/$2 per million tokens in and out against $1/$4.05 for Inkling FP4. Billed on Allocate: $0.48/$2.14 against $1.07/$4.33.
Which has the bigger context window?
Inkling FP4: 524,288 tokens (512K) against 202,752 (198K) for GLM 4.7 FP8.
Can I fine-tune Inkling FP4 or GLM 4.7 FP8?
Both publish open weights (Inkling FP4: Apache 2.0; GLM 4.7 FP8: MIT), 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.