AllocateGLM 4.6 Fp8 vs GLM 4.7 FP8
On provider list prices, GLM 4.7 FP8 costs $0.45 per million input tokens against $0.60 for GLM 4.6 Fp8: 1.3x apart. Output is $2 against $2.20 (1.1x).
Specifications and provider list prices from the Allocate catalog, checked 2026-09-12.
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 $1,490 on GLM 4.6 Fp8 at list: a gap of $250, or 1.2x.
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, GLM 4.6 Fp8 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 $0.60/$2.20 for GLM 4.6 Fp8. Billed on Allocate: $0.48/$2.14 against $0.64/$2.35.
Which has the bigger context window?
They match: both read 202,752 tokens (198K) per request.
Can I fine-tune GLM 4.6 Fp8 or GLM 4.7 FP8?
Both publish open weights (GLM 4.6 Fp8: MIT; 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 do not 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.