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DeepSeek R1 0528 NVFP4 vs Qwen2.5-VL (72B) Instruct

On provider list prices, Qwen2.5-VL (72B) Instruct costs $1.95 per million input tokens against $3 for DeepSeek R1 0528 NVFP4: 1.5x apart. Output is $8 against $7. On Allocate both bill at list plus the 7% transaction fee.

DeepSeek R1 0528 NVFP4 Qwen2.5-VL (72B) Instruct
LabDeepseekQwen
AccessOpen weightsOpen weights
Context window160K tokens32K tokens
List price, input$3 / M tokens$1.95 / M tokens
List price, output$7 / M tokens$8 / M tokens
Cached inputn/an/a
LicenseMITQwen 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 $5,140 a month on Qwen2.5-VL (72B) Instruct and $6,050 on DeepSeek R1 0528 NVFP4 at list: a gap of $910, or 1.2x.

DeepSeek R1 0528 NVFP4 reads 160K tokens per request against 32K for Qwen2.5-VL (72B) Instruct, 5.0x the window. That decides which one can take whole documents without splitting them.

Qwen2.5-VL (72B) Instruct$1.95$8
DeepSeek R1 0528 NVFP4$3$7
InputOutput

Choose DeepSeek R1 0528 NVFP4 for

  • The longer context window (160K vs 32K tokens)
  • Fine-tuning under a permissive license (MIT)
DeepSeek R1 0528 NVFP4 details

Choose Qwen2.5-VL (72B) Instruct for

  • The lower list price ($1.95 in / $8 out per M tokens)
Qwen2.5-VL (72B) Instruct details

Common questions

Which is cheaper, DeepSeek R1 0528 NVFP4 or Qwen2.5-VL (72B) Instruct?

Qwen2.5-VL (72B) Instruct, on this workload shape. At list prices it is $1.95/$8 per million tokens in and out against $3/$7 for DeepSeek R1 0528 NVFP4. Billed on Allocate: $2.09/$8.56 against $3.21/$7.49, list plus 7%.

Which has the bigger context window?

DeepSeek R1 0528 NVFP4: 163,840 tokens (160K) against 32,768 (32K) for Qwen2.5-VL (72B) Instruct.

Can I fine-tune DeepSeek R1 0528 NVFP4 or Qwen2.5-VL (72B) Instruct?

Both publish open weights (DeepSeek R1 0528 NVFP4: MIT; Qwen2.5-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

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Run the numbers on your workload

LLM price comparisonAgent cost calculatorDeepSeek R1 0528 NVFP4Qwen2.5-VL (72B) 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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