AllocateGemma 4 31B-it FP8 vs Glm 4.5 Air Fp8
On provider list prices, Glm 4.5 Air Fp8 costs $0.20 per million input tokens against $0.39 for Gemma 4 31B-it FP8: 1.9x apart. Output is $1.10 against $0.97. On Allocate both bill at list plus the 7% transaction fee.
Gemma 4 31B-it FP8G Glm 4.5 Air Fp8Specifications 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 $625 a month on Glm 4.5 Air Fp8 and $807.50 on Gemma 4 31B-it FP8 at list: a gap of $182.50, or 1.3x.
Gemma 4 31B-it FP8 reads 256K tokens per request against 128K for Glm 4.5 Air Fp8, 2.0x the window. That decides which one can take whole documents without splitting them.
Choose Gemma 4 31B-it FP8 for
- The longer context window (256K vs 128K tokens)
- Fine-tuning under a permissive license (Apache 2.0)
Choose Glm 4.5 Air Fp8 for
- The lower list price ($0.20 in / $1.10 out per M tokens)
- Fine-tuning under a permissive license (MIT)
Common questions
Which is cheaper, Gemma 4 31B-it FP8 or Glm 4.5 Air Fp8?
Glm 4.5 Air Fp8, on this workload shape. At list prices it is $0.20/$1.10 per million tokens in and out against $0.39/$0.97 for Gemma 4 31B-it FP8. Billed on Allocate: $0.21/$1.18 against $0.42/$1.04, list plus 7%.
Which has the bigger context window?
Gemma 4 31B-it FP8: 262,144 tokens (256K) against 131,072 (128K) for Glm 4.5 Air Fp8.
Can I fine-tune Gemma 4 31B-it FP8 or Glm 4.5 Air Fp8?
Both publish open weights (Gemma 4 31B-it FP8: Apache 2.0; Glm 4.5 Air 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.