AllocateNous Hermes 2 Mixtral 8X7B Dpo vs Pearl-ai Gemma-4-31B-it-pearl
On provider list prices, Pearl-ai Gemma-4-31B-it-pearl costs $0.28 per million input tokens against $0.60 for Nous Hermes 2 Mixtral 8X7B Dpo: 2.1x apart. Output is $0.86 against $0.60. On Allocate both bill at list plus the 7% transaction fee.
Specifications 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 $637 a month on Pearl-ai Gemma-4-31B-it-pearl and $930 on Nous Hermes 2 Mixtral 8X7B Dpo at list: a gap of $293, or 1.5x.
Pearl-ai Gemma-4-31B-it-pearl reads 256K tokens per request against 32K for Nous Hermes 2 Mixtral 8X7B Dpo, 8.0x the window. That decides which one can take whole documents without splitting them.
Choose Nous Hermes 2 Mixtral 8X7B Dpo for
- Fine-tuning under a permissive license (Apache 2.0)
Choose Pearl-ai Gemma-4-31B-it-pearl for
- The lower list price ($0.28 in / $0.86 out per M tokens)
- The longer context window (256K vs 32K tokens)
Common questions
Which is cheaper, Nous Hermes 2 Mixtral 8X7B Dpo or Pearl-ai Gemma-4-31B-it-pearl?
Pearl-ai Gemma-4-31B-it-pearl, on this workload shape. At list prices it is $0.28/$0.86 per million tokens in and out against $0.60/$0.60 for Nous Hermes 2 Mixtral 8X7B Dpo. Billed on Allocate: $0.30/$0.92 against $0.64/$0.64, list plus 7%.
Which has the bigger context window?
Pearl-ai Gemma-4-31B-it-pearl: 262,144 tokens (256K) against 32,768 (32K) for Nous Hermes 2 Mixtral 8X7B Dpo.
Can I fine-tune Nous Hermes 2 Mixtral 8X7B Dpo or Pearl-ai Gemma-4-31B-it-pearl?
Both publish open weights (Nous Hermes 2 Mixtral 8X7B Dpo: Apache 2.0; Pearl-ai Gemma-4-31B-it-pearl: Not listed), 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.