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Comparisons

Qwen2 72B Instruct vs Qwen3-VL-32B-Instruct

On provider list prices, Qwen2 72B Instruct costs $0.90 per million input tokens against $0.50 for Qwen3-VL-32B-Instruct: effectively level. Output is $0.90 against $1.50 (1.7x). On Allocate both bill at list plus the 7% transaction fee.

Qwen2 72B Instruct Qwen3-VL-32B-Instruct
LabTogethercomputerQwen
AccessOpen weightsOpen weights
Context window32K tokens256K tokens
List price, input$0.9 / M tokens$0.5 / M tokens
List price, output$0.9 / M tokens$1.5 / M tokens
Cached inputn/an/a
LicenseQwen licenseApache 2.0
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 $1,125 a month on Qwen3-VL-32B-Instruct and $1,395 on Qwen2 72B Instruct at list: a gap of $270, or 1.2x.

Qwen3-VL-32B-Instruct reads 256K tokens per request against 32K for Qwen2 72B Instruct, 8.0x the window. That decides which one can take whole documents without splitting them.

Qwen3-VL-32B-Instruct$0.50$1.50
Qwen2 72B Instruct$0.90$0.90
InputOutput

Choose Qwen2 72B Instruct for

  • Training toward a model you own
Qwen2 72B Instruct details

Choose Qwen3-VL-32B-Instruct for

  • The lower list price ($0.50 in / $1.50 out per M tokens)
  • The longer context window (256K vs 32K tokens)
  • Fine-tuning under a permissive license (Apache 2.0)
Qwen3-VL-32B-Instruct details

Common questions

Which is cheaper, Qwen2 72B Instruct or Qwen3-VL-32B-Instruct?

Qwen3-VL-32B-Instruct, on this workload shape. At list prices it is $0.50/$1.50 per million tokens in and out against $0.90/$0.90 for Qwen2 72B Instruct. Billed on Allocate: $0.54/$1.60 against $0.96/$0.96, list plus 7%.

Which has the bigger context window?

Qwen3-VL-32B-Instruct: 262,144 tokens (256K) against 32,768 (32K) for Qwen2 72B Instruct.

Can I fine-tune Qwen2 72B Instruct or Qwen3-VL-32B-Instruct?

Both publish open weights (Qwen2 72B Instruct: Qwen license; Qwen3-VL-32B-Instruct: Apache 2.0), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.

Related comparisons

Qwen2 72B Instruct vs Meta Llama 3.1 70B Instruct TurboQwen2 72B Instruct vs Meta Llama 3 70B Instruct TurboQwen3-VL-32B-Instruct vs Meta Llama 3.3 70B Instruct Turbo

Run the numbers on your workload

LLM price comparisonAgent cost calculatorQwen2 72B InstructQwen3-VL-32B-Instruct

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.

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