Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.3-Codex-Spark is clearly ahead on the aggregate, 87 to 62. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.3-Codex-Spark's sharpest advantage is in coding, where it averages 82.3 against 45.9. The single biggest benchmark swing on the page is SWE-bench Verified, 80 to 40.
GPT-5.3-Codex-Spark gives you the larger context window at 256K, compared with 200K for GLM-4.7-Flash.
Pick GPT-5.3-Codex-Spark if you want the stronger benchmark profile. GLM-4.7-Flash only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GPT-5.3-Codex-Spark
85.6
GLM-4.7-Flash
61.3
GPT-5.3-Codex-Spark
82.3
GLM-4.7-Flash
45.9
GPT-5.3-Codex-Spark
88.3
GLM-4.7-Flash
62.5
GPT-5.3-Codex-Spark
92.7
GLM-4.7-Flash
69.7
GPT-5.3-Codex-Spark
78.3
GLM-4.7-Flash
54.1
GPT-5.3-Codex-Spark
92
GLM-4.7-Flash
84
GPT-5.3-Codex-Spark
90.8
GLM-4.7-Flash
81.8
GPT-5.3-Codex-Spark
96.7
GLM-4.7-Flash
74
GPT-5.3-Codex-Spark is ahead overall, 87 to 62. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 80 and 40.
GPT-5.3-Codex-Spark has the edge for knowledge tasks in this comparison, averaging 78.3 versus 54.1. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for coding in this comparison, averaging 82.3 versus 45.9. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for math in this comparison, averaging 96.7 versus 74. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for reasoning in this comparison, averaging 92.7 versus 69.7. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for agentic tasks in this comparison, averaging 85.6 versus 61.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for multimodal and grounded tasks in this comparison, averaging 88.3 versus 62.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for instruction following in this comparison, averaging 92 versus 84. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.3-Codex-Spark has the edge for multilingual tasks in this comparison, averaging 90.8 versus 81.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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