Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 Pro is clearly ahead on the aggregate, 90 to 42. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2 Pro's sharpest advantage is in reasoning, where it averages 95.2 against 31.3. The single biggest benchmark swing on the page is LongBench v2, 93 to 30.
GPT-5.2 Pro is also the more expensive model on tokens at $25.00 input / $150.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Phi-4. That is roughly Infinityx on output cost alone. GPT-5.2 Pro is the reasoning model in the pair, while Phi-4 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GPT-5.2 Pro gives you the larger context window at 400K, compared with 16K for Phi-4.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. Phi-4 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.2 Pro
85.9
Phi-4
38.3
GPT-5.2 Pro
84.8
Phi-4
55
GPT-5.2 Pro
96
Phi-4
46.8
GPT-5.2 Pro
95.2
Phi-4
31.3
GPT-5.2 Pro
81.5
Phi-4
53.8
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
GPT-5.2 Pro
93.4
Phi-4
67.2
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
GPT-5.2 Pro is ahead overall, 90 to 42. The biggest single separator in this matchup is LongBench v2, where the scores are 93 and 30.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 53.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for coding in this comparison, averaging 84.8 versus 55. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for reasoning in this comparison, averaging 95.2 versus 31.3. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for agentic tasks in this comparison, averaging 85.9 versus 38.3. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 96 versus 46.8. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multilingual tasks in this comparison, averaging 93.4 versus 67.2. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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