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GPT-5.5 vs Qwen3 235B A22B Instruct 2507 FP8 Throughput

On provider list prices, Qwen3 235B A22B Instruct 2507 FP8 Throughput costs $0.20 per million input tokens against $5 for GPT-5.5: 25.0x apart. Output is $0.60 against $30 (50.0x). On Allocate both bill at list plus the 7% transaction fee.

GPT-5.5 Qwen3 235B A22B Instruct 2507 FP8 Throughput
LabOpenAIQwen
AccessAPI onlyOpen weights
Context window400K tokens256K tokens
List price, input$5 / M tokens$0.2 / M tokens
List price, output$30 / M tokens$0.6 / M tokens
Cached input$0.5 / M tokensn/a
LicenseProprietary APIApache 2.0
Fine-tunableNoYes

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 $450 a month on Qwen3 235B A22B Instruct 2507 FP8 Throughput and $16,500 on GPT-5.5 at list: a gap of $16,050, or 36.7x.

GPT-5.5 reads 400K tokens per request against 256K for Qwen3 235B A22B Instruct 2507 FP8 Throughput, 1.5x the window. That decides which one can take whole documents without splitting them.

Qwen3 235B A22B Instruct 2507 FP8 Throughput$0.20$0.60
GPT-5.5$5$30
InputOutput

Choose GPT-5.5 for

  • Complex tool-using agents
  • Code generation
  • General assistants
GPT-5.5 details

Choose Qwen3 235B A22B Instruct 2507 FP8 Throughput for

  • The lower list price ($0.20 in / $0.60 out per M tokens)
  • Open weights you can fine-tune and own
  • Fine-tuning under a permissive license (Apache 2.0)
Qwen3 235B A22B Instruct 2507 FP8 Throughput details

Common questions

Which is cheaper, GPT-5.5 or Qwen3 235B A22B Instruct 2507 FP8 Throughput?

Qwen3 235B A22B Instruct 2507 FP8 Throughput, on this workload shape. At list prices it is $0.20/$0.60 per million tokens in and out against $5/$30 for GPT-5.5. Billed on Allocate: $0.21/$0.64 against $5.35/$32.10, list plus 7%.

Which has the bigger context window?

GPT-5.5: 400,000 tokens (400K) against 262,144 (256K) for Qwen3 235B A22B Instruct 2507 FP8 Throughput.

Can I fine-tune GPT-5.5 or Qwen3 235B A22B Instruct 2507 FP8 Throughput?

Qwen3 235B A22B Instruct 2507 FP8 Throughput publishes open weights (Apache 2.0) and can be fine-tuned on your own data. GPT-5.5 is a closed model served over API; its weights are not available.

Related comparisons

GPT-5.5 vs Qwen3.7 MaxQwen3 235B A22B Instruct 2507 FP8 Throughput vs Qwen3.7 MaxGPT-5.5 vs Qwen3.5 397B A17bQwen3 235B A22B Instruct 2507 FP8 Throughput vs Qwen3.5 397B A17bQwen3 235B A22B Instruct 2507 FP8 Throughput vs Qwen3-VL-8B-InstructGPT-5.5 vs OpenAI GPT-OSS 120B

Run the numbers on your workload

LLM price comparisonAgent cost calculatorGPT-5.5Qwen3 235B A22B Instruct 2507 FP8 Throughput

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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