GPT-5.4 nanovsQwen3-Coder
GPT-5.4 nano | Qwen3-Coder | |
|---|---|---|
| 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. | — | 480B |
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. | — | 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. | $0.20 | $1.00 |
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. | $1.25 | $5.00 |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | $0.02 | — |
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.20Azure | $0.22Google |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $1.25Azure | $1.00DeepInfra |
| Benchmarks | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | 14% | 20% |
| BenchmarksPublished by one model only | ||
Humanity's Last Exam · with toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | 37.7% | — |
OSWorld-VerifiedAgentic computer use — Can the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better. | 39% | — |
| Overview | ||
| Company | OpenAI | Qwen |
| Release date | Mar 17 2026 | Jul 22 2025 |
| Access | Proprietary | Open Weight |
Other comparisons
GPT-5.4 nanovsClaude Fable 5.1Qwen3-CodervsClaude Fable 5.1GPT-5.4 nanovsGemini 3.8 FlashQwen3-CodervsGemini 3.8 FlashGPT-5.4 nanovsMuse Spark 1.3Qwen3-CodervsMuse Spark 1.3GPT-5.4 nanovsGrok 4.6Qwen3-CodervsGrok 4.6GPT-5.4 nanovsDeepSeek-V4.1-FlashQwen3-CodervsDeepSeek-V4.1-FlashGPT-5.4 nanovsMistral Medium 3.5Qwen3-CodervsMistral Medium 3.5
Frequently asked questions
Qwen3-Coder leads GPT-5.4 nano on 1 of the 1 benchmark they both report (BullshitBench v2). GPT-5.4 nano is cheaper on both input and output: $0.20 vs $1.00 per million input tokens, and $1.25 vs $5.00 per million output tokens. Figures are base-tier rates. Qwen3-Coder shipped 238 days before GPT-5.4 nano, so benchmark comparisons should account for the intervening progress.
GPT-5.4 nano is proprietary, while Qwen3-Coder is open weight.
On BullshitBench v2, Qwen3-Coder leads at 20% vs GPT-5.4 nano at 14%.