# 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.

## Specifications

| | GPT-5.5 | Qwen3 235B A22B Instruct 2507 FP8 Throughput |
| --- | --- | --- |
| Lab | OpenAI | Qwen |
| Access | API only | Open weights |
| Context window | 400K tokens | 256K tokens |
| List price, input | $5 / M tokens | $0.20 / M tokens |
| List price, output | $30 / M tokens | $0.60 / M tokens |
| Cached input | $0.50 / M tokens | n/a |
| License | Proprietary API | Apache 2.0 |
| Fine-tunable | No | 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 $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.

## Choose GPT-5.5 for

- Complex tool-using agents
- Code generation
- General assistants

## 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)

## 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.

---

[HTML page](https://allocate.network/compare/gpt-5-5-vs-qwen-qwen3-235b-a22b-instruct-2507-tput) · [GPT-5.5](https://allocate.network/models/gpt-5-5.md) · [Qwen3 235B A22B Instruct 2507 FP8 Throughput](https://allocate.network/models/qwen-qwen3-235b-a22b-instruct-2507-tput.md) · [Machine-readable catalog](https://allocate.network/catalog.json)