GPT-5.2-Codex
According to BenchLM.ai, GPT-5.2-Codex ranks #29 out of 119 models on the provisional leaderboard with an overall score of 76/100. It does not yet have enough sourced coverage for BenchLM's verified leaderboard. This places it in the mid-tier of AI models, with strengths in specific benchmark categories.
GPT-5.2-Codex is a proprietary model with a 400K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.
This profile currently has 19 of 225 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Its strongest category is Mathematics (#3), while its weakest is Coding (#25). This performance profile makes it particularly strong for mathematical reasoning, scientific computing, and quantitative analysis.
Ranking Distribution
Category rank across 8 benchmark categories — sorted by best rank
Category Performance
Scores across all benchmark categories (0-100 scale)
Category Breakdown
Agentic
Coding
#25Reasoning
#11Knowledge
#23Math
#3Multilingual
#11Multimodal
#11Inst. Following
#11Chatbot Arena Performance
Benchmark Details
Only benchmark rows with an attached exact-source record are shown here. Source-unverified manual rows and generated rows are hidden from model pages.
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Frequently Asked Questions
How does GPT-5.2-Codex perform overall in AI benchmarks?
GPT-5.2-Codex currently ranks #29 out of 119 models on BenchLM's provisional leaderboard with an overall score of 76 (estimated). It is created by OpenAI and features a 400K context window.
Is GPT-5.2-Codex good for knowledge and understanding?
GPT-5.2-Codex ranks #23 out of 119 models in knowledge and understanding benchmarks with an average score of 77.8. There are stronger options in this category.
Is GPT-5.2-Codex good for coding and programming?
GPT-5.2-Codex ranks #25 out of 119 models in coding and programming benchmarks with an average score of 78.1. There are stronger options in this category.
Is GPT-5.2-Codex good for reasoning and logic?
GPT-5.2-Codex ranks #11 out of 119 models in reasoning and logic benchmarks with an average score of 87.3. There are stronger options in this category.
Is GPT-5.2-Codex good for agentic tool use and computer tasks?
GPT-5.2-Codex has visible benchmark coverage in agentic tool use and computer tasks, but BenchLM does not currently assign it a global category rank there.
Is GPT-5.2-Codex good for multimodal and grounded tasks?
GPT-5.2-Codex ranks #11 out of 119 models in multimodal and grounded tasks benchmarks with an average score of 88.2. There are stronger options in this category.
Is GPT-5.2-Codex good for instruction following?
GPT-5.2-Codex ranks #11 out of 119 models in instruction following benchmarks with an average score of 91.6. There are stronger options in this category.
Does GPT-5.2-Codex have full benchmark coverage on BenchLM?
Not yet. GPT-5.2-Codex currently has 19 published benchmark scores out of the 225 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
What is the context window size of GPT-5.2-Codex?
GPT-5.2-Codex has a context window of 400K, which determines how much text it can process in a single interaction.
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