Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | — | 32B |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 128k | 32k |
| These models have no shared benchmark scores. | ||
LiveCodeBenchCompetitive coding — Coding problems published so recently the AI can't have seen them in training — a contamination-free test of raw programming skill. Higher is better. | — | 50% |
| Overview | ||
| Company | OpenAI | Qwen |
| Release date | Feb 12 2026 | Nov 28 2024 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
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GPT-5.3-Codex-Spark and QwQ-32B-Preview don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. QwQ-32B-Preview shipped 441 days before GPT-5.3-Codex-Spark, so benchmark comparisons should account for the intervening progress.
Context windows are 128k (GPT-5.3-Codex-Spark) vs 32k (QwQ-32B-Preview). GPT-5.3-Codex-Spark is closed, while QwQ-32B-Preview is open weight.
Direct benchmark comparisons are unavailable — GPT-5.3-Codex-Spark and QwQ-32B-Preview don't publish scores on any of the same benchmarks.