# MiniMax M3 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 $0.30 for MiniMax M3: 1.5x apart. Output is $0.60 against $1.20 (2.0x). On Allocate both bill at list plus the 7% transaction fee.

## Specifications

| | MiniMax M3 | Qwen3 235B A22B Instruct 2507 FP8 Throughput |
| --- | --- | --- |
| Lab | MiniMaxAI | Qwen |
| Access | API only | Open weights |
| Context window | 512K tokens | 256K tokens |
| List price, input | $0.30 / M tokens | $0.20 / M tokens |
| List price, output | $1.20 / M tokens | $0.60 / M tokens |
| Cached input | $0.06 / 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 $780 on MiniMax M3 at list: a gap of $330, or 1.7x.

MiniMax M3 reads 512K tokens per request against 256K for Qwen3 235B A22B Instruct 2507 FP8 Throughput, 2.0x the window. That decides which one can take whole documents without splitting them.

## Choose MiniMax M3 for

- The longer context window (512K vs 256K tokens)
- Published cached-input pricing ($0.06 per M tokens)

## 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, MiniMax M3 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 $0.30/$1.20 for MiniMax M3. Billed on Allocate: $0.21/$0.64 against $0.32/$1.28, list plus 7%.

### Which has the bigger context window?

MiniMax M3: 524,288 tokens (512K) against 262,144 (256K) for Qwen3 235B A22B Instruct 2507 FP8 Throughput.

### Can I fine-tune MiniMax M3 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. MiniMax M3 is a closed model served over API; its weights are not available.

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[HTML page](https://allocate.network/compare/minimaxai-minimax-m3-vs-qwen-qwen3-235b-a22b-instruct-2507-tput) · [MiniMax M3](https://allocate.network/models/minimaxai-minimax-m3.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)