GPT-5.3 Codex leads on the shared-benchmark average
Ahead on 6 of 8 shared benchmarks, averaging 3.4 points higher
Summarised only from the 8 percentage-scale benchmarks scored by every selected model; details are below.
“Best available” takes each model’s best recorded non-parallel result in the metric’s stated direction per benchmark, so it may combine modes into a virtual configuration that does not exist. Read it with the mode breakdown.

GPT-5.3 Codex
OpenAI
Benchmark-by-benchmark comparison. Changing the thinking mode or tool filters updates the chart and table below.
“Best available” picks the best non-parallel result in the metric’s stated direction separately for each benchmark. The resulting series can combine several reasoning levels and is not one reproducible runtime configuration. Choose a mode filter to compare like-for-like runs.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
Each axis is the mean percentage score of one benchmark domain. It is an average, not a capability rating.
Relative edge: Agent能力评测 +4.9 / Relative gap: 指令跟随 -2.2
Relative edge: 指令跟随 +2.2 / Relative gap: Agent能力评测 -4.9
Method: for each model and benchmark, all scores in the current mode scope are averaged (not the best score), then those benchmark scores are averaged within each domain. Only benchmarks scored on a 0-100 scale by at least two of the selected models count — Elo and rating-scale benchmarks such as Codeforces or Arena are excluded, because averaging a 1500 rating with an 85% accuracy produces a meaningless number. Missing values are not counted as zero, and the averages are unweighted, so domains with harder benchmarks read lower.
Every model and runtime mode, benchmark by benchmark. Values are comparable along a row, not between different benchmarks.
9 benchmarks with comparable scores. Each model shows its best score; mode label is displayed below.
| Benchmark | GPT-5.3 Codex | GPT-5.2-Codex |
|---|---|---|
16.90Thinking Level · Extra High | 8.70Thinking Level · Extra High | |
42.50Thinking Level · Extra High | 35.70Thinking Level · Extra High | |
72.76Thinking Level · High | 73.98Standard Mode | |
91.50Thinking Level · Extra High | 89.90Thinking Level · Extra High | |
53.00Thinking Level · Extra High | Tools | 37.10Thinking Level · Extra High | Tools | |
86.00Thinking Level · Extra High | Tools | 92.10Thinking Level · Extra High | Tools | |
75.40Thinking Level · Extra High | 77.60Thinking Level · Extra High | |
83.30Thinking Level · Extra High | 82.30Thinking Level · Extra High | |
78.50Thinking Level · Extra High | 76.30Thinking Level · Extra High |
Official list prices per model API, split by input and output. Unit: USD per 1M tokens.
Architecture, licensing and API modalities. "Not provided" means the field is missing from our database.
| Features & specs | GPT-5.3 CodexOpenAI | GPT-5.2-CodexOpenAI |
|---|---|---|
Core specsRelease | 2026-02-05 | 2025-12-18 |
Context length | 400K | — |
Max output length | 128,000 tokens | Not provided |
Architecture | Undisclosed | Undisclosed |
Runtime modes | 关闭低中高极高深度 | 关闭低中高极高开启 |
Availability & licensingCode availability | Not public | Not public |
Weight availability | Not public | Not public |
Use & commercial terms | Official service only; subject to provider terms | Official service only; subject to provider terms |
API modality supportText Input/Output | Input:YesOutput:Yes | Input:YesOutput:Yes |
Image Input/Output | Input:YesOutput:No | Input:YesOutput:No |
ResourcesPaper / report | Introducing GPT-5.3-Codex | Introducing GPT-5.2-Codex |

GPT-5.2-Codex
OpenAI