Comparisons

Qwen 3.5 vs Inkling

On provider list prices, Qwen 3.5 costs $0.60 per million input tokens against $1.87 for Inkling: 3.1x apart. Output is $3.60 against $4.68 (1.3x). On Allocate both bill at list plus the 7% transaction fee.

Qwen 3.5 Inkling
LabQwenThinking Machines
AccessOpen weightsOpen weights
Context window256K tokens1M tokens
List price, input$0.6 / M tokens$1.87 / M tokens
List price, output$3.6 / M tokens$4.68 / M tokens
Cached input$0.35 / M tokens$0.374 / M tokens
LicenseApache 2.0Apache 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 $1,980 a month on Qwen 3.5 and $3,882 on Inkling at list: a gap of $1,902, or 2.0x.

Inkling reads 1M tokens per request against 256K for Qwen 3.5, 3.8x the window. That decides which one can take whole documents without splitting them.

Qwen 3.5$0.60$3.60
Inkling$1.87$4.68
InputOutput

Choose Qwen 3.5 for

  • Multilingual support agents
  • Translation-adjacent workflows
  • Fine-tuning under Apache 2.0
Qwen 3.5 details

Choose Inkling for

  • The longer context window (1M vs 256K tokens)
  • Fine-tuning under a permissive license (Apache 2.0)
Inkling details

Common questions

Which is cheaper, Qwen 3.5 or Inkling?

Qwen 3.5, on this workload shape. At list prices it is $0.60/$3.60 per million tokens in and out against $1.87/$4.68 for Inkling. Billed on Allocate: $0.64/$3.85 against $2.00/$5.01, list plus 7%.

Which has the bigger context window?

Inkling: 1,000,000 tokens (1M) against 262,144 (256K) for Qwen 3.5.

Can I fine-tune Qwen 3.5 or Inkling?

Both publish open weights (Qwen 3.5: Apache 2.0; Inkling: Apache 2.0), 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.