AllocateMixtral-8x7B Instruct v0.1 vs Glm 4.5 Air Fp8
On provider list prices, Mixtral-8x7B Instruct v0.1 costs $0.60 per million input tokens against $0.20 for Glm 4.5 Air Fp8: effectively level. Output is $0.60 against $1.10 (1.8x).
Mixtral-8x7B Instruct v0.1G Glm 4.5 Air 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 $625 a month on Glm 4.5 Air Fp8 and $930 on Mixtral-8x7B Instruct v0.1 at list: a gap of $305, or 1.5x.
Glm 4.5 Air Fp8 reads 128K tokens per request against 32K for Mixtral-8x7B Instruct v0.1, 4.0x the window. That decides which one can take whole documents without splitting them.
Choose Mixtral-8x7B Instruct v0.1 for
- 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)
- The longer context window (128K vs 32K tokens)
- Fine-tuning under a permissive license (MIT)
Common questions
Which is cheaper, Mixtral-8x7B Instruct v0.1 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 $0.60/$0.60 for Mixtral-8x7B Instruct v0.1. Billed on Allocate: $0.21/$1.18 against $0.64/$0.64.
Which has the bigger context window?
Glm 4.5 Air Fp8: 131,072 tokens (128K) against 32,768 (32K) for Mixtral-8x7B Instruct v0.1.
Can I fine-tune Mixtral-8x7B Instruct v0.1 or Glm 4.5 Air Fp8?
Both publish open weights (Mixtral-8x7B Instruct v0.1: 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 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.