GPT-5.3-CodexvsQwen3-Coder
GPT-5.3-Codex | 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. | $1.75 | $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. | $14.00 | $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. | $0.175 | — |
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. | $1.75Azure | $0.22Google |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $14.00Azure | $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. | 24% | 20% |
| BenchmarksPublished by one model only | ||
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 85% | — |
Next.js EvalsNext.js coding — Vercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | 68% | — |
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. | 64.7% | — |
| Overview | ||
| Company | OpenAI | Qwen |
| Release date | Feb 5 2026 | Jul 22 2025 |
| Access | Proprietary | Open Weight |
Other comparisons
GPT-5.3-CodexvsClaude Fable 5.1Qwen3-CodervsClaude Fable 5.1GPT-5.3-CodexvsGemini 3.8 FlashQwen3-CodervsGemini 3.8 FlashGPT-5.3-CodexvsMuse Spark 1.3Qwen3-CodervsMuse Spark 1.3GPT-5.3-CodexvsGrok 4.6Qwen3-CodervsGrok 4.6GPT-5.3-CodexvsDeepSeek-V4.1-FlashQwen3-CodervsDeepSeek-V4.1-FlashGPT-5.3-CodexvsMistral Medium 3.5Qwen3-CodervsMistral Medium 3.5
Frequently asked questions
GPT-5.3-Codex leads Qwen3-Coder on 1 of the 1 benchmark they both report (BullshitBench v2). Qwen3-Coder is cheaper on both input and output: $1.00 vs $1.75 per million input tokens, and $5.00 vs $14.00 per million output tokens. Figures are base-tier rates. Qwen3-Coder shipped 198 days before GPT-5.3-Codex, so benchmark comparisons should account for the intervening progress.
GPT-5.3-Codex is proprietary, while Qwen3-Coder is open weight.
On BullshitBench v2, GPT-5.3-Codex leads at 24% vs Qwen3-Coder at 20%.