Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.7 (Adaptive)
85
GPT-5.3 Codex
86
Verified leaderboard positions: Claude Opus 4.7 (Adaptive) #7 · GPT-5.3 Codex unranked
Pick GPT-5.3 Codex if you want the stronger benchmark profile. Claude Opus 4.7 (Adaptive) only becomes the better choice if coding is the priority or you need the larger 1M context window.
Agentic
+3.4 difference
Coding
+9.8 difference
Claude Opus 4.7 (Adaptive)
GPT-5.3 Codex
$5 / $25
$1.75 / $14
N/A
79 t/s
N/A
88.26s
1M
400K
Pick GPT-5.3 Codex if you want the stronger benchmark profile. Claude Opus 4.7 (Adaptive) only becomes the better choice if coding is the priority or you need the larger 1M context window.
GPT-5.3 Codex finishes one point ahead on BenchLM's provisional leaderboard, 86 to 85. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Claude Opus 4.7 (Adaptive) is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $1.75 input / $14.00 output per 1M tokens for GPT-5.3 Codex. Claude Opus 4.7 (Adaptive) gives you the larger context window at 1M, compared with 400K for GPT-5.3 Codex.
GPT-5.3 Codex is ahead on BenchLM's provisional leaderboard, 86 to 85. The biggest single separator in this matchup is OSWorld-Verified, where the scores are 78% and 64.7%.
Claude Opus 4.7 (Adaptive) has the edge for coding in this comparison, averaging 72.9 versus 63.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Claude Opus 4.7 (Adaptive) has the edge for agentic tasks in this comparison, averaging 74.9 versus 71.5. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
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