Comparisons

Cogito v2.1 671B vs Qwen2-VL (72B) Instruct

On provider list prices, Qwen2-VL (72B) Instruct costs $1.20 per million input tokens against $1.25 for Cogito v2.1 671B: effectively level. Output is $1.20 against $1.25. On Allocate both bill at list plus the 7% transaction fee.

C Cogito v2.1 671B Qwen2-VL (72B) Instruct
LabDeepcogitoQwen
AccessOpen weightsOpen weights
Context window160K tokens32K tokens
List price, input$1.25 / M tokens$1.2 / M tokens
List price, output$1.25 / M tokens$1.2 / M tokens
Cached inputn/an/a
LicenseNot listedQwen license
Fine-tunableYesYes

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 $1,860 a month on Qwen2-VL (72B) Instruct and $1,938 on Cogito v2.1 671B at list: a gap of $77.50.

Cogito v2.1 671B reads 160K tokens per request against 32K for Qwen2-VL (72B) Instruct, 5.0x the window. That decides which one can take whole documents without splitting them.

Qwen2-VL (72B) Instruct$1.20$1.20
Cogito v2.1 671B$1.25$1.25
InputOutput

Choose Cogito v2.1 671B for

  • The longer context window (160K vs 32K tokens)
Cogito v2.1 671B details

Choose Qwen2-VL (72B) Instruct for

  • The lower list price ($1.20 in / $1.20 out per M tokens)
Qwen2-VL (72B) Instruct details

Common questions

Which is cheaper, Cogito v2.1 671B or Qwen2-VL (72B) Instruct?

Qwen2-VL (72B) Instruct, on this workload shape. At list prices it is $1.20/$1.20 per million tokens in and out against $1.25/$1.25 for Cogito v2.1 671B. Billed on Allocate: $1.28/$1.28 against $1.34/$1.34, list plus 7%.

Which has the bigger context window?

Cogito v2.1 671B: 163,840 tokens (160K) against 32,768 (32K) for Qwen2-VL (72B) Instruct.

Can I fine-tune Cogito v2.1 671B or Qwen2-VL (72B) Instruct?

Both publish open weights (Cogito v2.1 671B: Not listed; Qwen2-VL (72B) Instruct: Qwen license), 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.