# Gemini 3.5 Flash 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 $1.50 for Gemini 3.5 Flash: 7.5x apart. Output is $0.60 against $9 (15.0x). On Allocate both bill at list plus the 7% transaction fee.

## Specifications

| | Gemini 3.5 Flash | Qwen3 235B A22B Instruct 2507 FP8 Throughput |
| --- | --- | --- |
| Lab | Google | Qwen |
| Access | API only | Open weights |
| Context window | 1M tokens | 256K tokens |
| List price, input | $1.50 / M tokens | $0.20 / M tokens |
| List price, output | $9 / M tokens | $0.60 / M tokens |
| Cached input | n/a | 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 $4,950 on Gemini 3.5 Flash at list: a gap of $4,500, or 11.0x.

Gemini 3.5 Flash reads 1M tokens per request against 256K for Qwen3 235B A22B Instruct 2507 FP8 Throughput, 3.8x the window. That decides which one can take whole documents without splitting them.

## Choose Gemini 3.5 Flash for

- High-volume support and triage
- Document extraction at scale
- Vision and OCR pipelines

## 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, Gemini 3.5 Flash 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 $1.50/$9 for Gemini 3.5 Flash. Billed on Allocate: $0.21/$0.64 against $1.60/$9.63, list plus 7%.

### Which has the bigger context window?

Gemini 3.5 Flash: 1,000,000 tokens (1M) against 262,144 (256K) for Qwen3 235B A22B Instruct 2507 FP8 Throughput.

### Can I fine-tune Gemini 3.5 Flash 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. Gemini 3.5 Flash is a closed model served over API; its weights are not available.

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[HTML page](https://allocate.network/compare/gemini-3-5-flash-vs-qwen-qwen3-235b-a22b-instruct-2507-tput) · [Gemini 3.5 Flash](https://allocate.network/models/gemini-3-5-flash.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)