# Qwen2.5 72B Instruct vs Qwen2.5 72B Instruct Turbo

On provider list prices, Qwen2.5 72B Instruct costs $1.20 per million input tokens against $1.20 for Qwen2.5 72B Instruct Turbo: effectively level. Output is $1.20 against $1.20. On Allocate both bill at list plus the 7% transaction fee.

## Specifications

| | Qwen2.5 72B Instruct | Qwen2.5 72B Instruct Turbo |
| --- | --- | --- |
| Lab | Qwen | Qwen |
| Access | Open weights | Open weights |
| Context window | 32K tokens | 128K tokens |
| List price, input | $1.20 / M tokens | $1.20 / M tokens |
| List price, output | $1.20 / M tokens | $1.20 / M tokens |
| Cached input | n/a | n/a |
| License | Qwen license | Qwen license |
| Fine-tunable | Yes | Yes |

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 Qwen2.5 72B Instruct and $1,860 on Qwen2.5 72B Instruct Turbo at list: a gap of $0.

Qwen2.5 72B Instruct Turbo reads 128K tokens per request against 32K for Qwen2.5 72B Instruct, 4.0x the window. That decides which one can take whole documents without splitting them.

## Choose Qwen2.5 72B Instruct for

- Training toward a model you own

## Choose Qwen2.5 72B Instruct Turbo for

- The longer context window (128K vs 32K tokens)

## Common questions

### Which is cheaper, Qwen2.5 72B Instruct or Qwen2.5 72B Instruct Turbo?

Qwen2.5 72B Instruct, on this workload shape. At list prices it is $1.20/$1.20 per million tokens in and out against $1.20/$1.20 for Qwen2.5 72B Instruct Turbo. Billed on Allocate: $1.28/$1.28 against $1.28/$1.28, list plus 7%.

### Which has the bigger context window?

Qwen2.5 72B Instruct Turbo: 131,072 tokens (128K) against 32,768 (32K) for Qwen2.5 72B Instruct.

### Can I fine-tune Qwen2.5 72B Instruct or Qwen2.5 72B Instruct Turbo?

Both publish open weights (Qwen2.5 72B Instruct: Qwen license; Qwen2.5 72B Instruct Turbo: Qwen license), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.

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[HTML page](https://allocate.network/compare/qwen-qwen2-5-72b-instruct-vs-qwen-qwen2-5-72b-instruct-turbo) · [Qwen2.5 72B Instruct](https://allocate.network/models/qwen-qwen2-5-72b-instruct.md) · [Qwen2.5 72B Instruct Turbo](https://allocate.network/models/qwen-qwen2-5-72b-instruct-turbo.md) · [Machine-readable catalog](https://allocate.network/catalog.json)