Comparisons /

Nous Hermes 2 Mixtral 8X7B Dpo vs Glm 4.5 Air Fp8

On provider list prices, Nous Hermes 2 Mixtral 8X7B Dpo 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).

N Nous Hermes 2 Mixtral 8X7B DpoG Glm 4.5 Air Fp8
LabNousresearchZ.ai
AccessOpen weightsOpen weights
Context window32K tokens128K tokens
List price, input$0.6 / M tokens$0.2 / M tokens
List price, output$0.6 / M tokens$1.1 / M tokens
Cached inputn/an/a
LicenseApache 2.0MIT
Fine-tunableYesYes

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 $625 a month on Glm 4.5 Air Fp8 and $930 on Nous Hermes 2 Mixtral 8X7B Dpo at list: a gap of $305, or 1.5x.

Glm 4.5 Air Fp8 reads 128K tokens per request against 32K for Nous Hermes 2 Mixtral 8X7B Dpo, 4.0x the window. That decides which one can take whole documents without splitting them.

Glm 4.5 Air Fp8$0.20$1.10
Nous Hermes 2 Mixtral 8X7B Dpo$0.60$0.60
InputOutput

Choose Nous Hermes 2 Mixtral 8X7B Dpo for

  • Fine-tuning under a permissive license (Apache 2.0)
Nous Hermes 2 Mixtral 8X7B Dpo details →

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)
Glm 4.5 Air Fp8 details →

Common questions

Which is cheaper, Nous Hermes 2 Mixtral 8X7B Dpo 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 Nous Hermes 2 Mixtral 8X7B Dpo. 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 Nous Hermes 2 Mixtral 8X7B Dpo.

Can I fine-tune Nous Hermes 2 Mixtral 8X7B Dpo or Glm 4.5 Air Fp8?

Both publish open weights (Nous Hermes 2 Mixtral 8X7B Dpo: 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.