GPT-4 TurbovsQwen3-Max
GPT-4 Turbo | Qwen3-Max | |
|---|---|---|
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | — | 1T |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | 128k | 256k |
| API pricingUSD per 1M tokens · lower wins · base tier | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $10.00 | $1.20 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | $30.00 | $6.00 |
| BenchmarksPublished by one model only | ||
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 42.5% | — |
| Overview | ||
| Company | OpenAI | Qwen |
| Release date | Nov 6 2023 | Sep 24 2025 |
| Access | Proprietary | Proprietary |
Other comparisons
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Frequently asked questions
GPT-4 Turbo and Qwen3-Max don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen3-Max is cheaper on both input and output: $1.20 vs $10.00 per million input tokens, and $6.00 vs $30.00 per million output tokens. Figures are base-tier rates. GPT-4 Turbo shipped 688 days before Qwen3-Max, so benchmark comparisons should account for the intervening progress.
Context windows are 128k (GPT-4 Turbo) vs 256k (Qwen3-Max).
Direct benchmark comparisons are unavailable — GPT-4 Turbo and Qwen3-Max don't publish scores on any of the same benchmarks.