Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.3 Codex
86
Kimi K2.6
85
Verified leaderboard positions: GPT-5.3 Codex unranked · Kimi K2.6 #9
Pick GPT-5.3 Codex if you want the stronger benchmark profile. Kimi K2.6 only becomes the better choice if coding is the priority or you want the cheaper token bill.
Agentic
+1.6 difference
Coding
+8.9 difference
GPT-5.3 Codex
Kimi K2.6
$1.75 / $14
$0.95 / $4
79 t/s
N/A
88.26s
N/A
400K
256K
Pick GPT-5.3 Codex if you want the stronger benchmark profile. Kimi K2.6 only becomes the better choice if coding is the priority or you want the cheaper token bill.
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.
GPT-5.3 Codex is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.95 input / $4.00 output per 1M tokens for Kimi K2.6. That is roughly 3.5x on output cost alone. GPT-5.3 Codex gives you the larger context window at 400K, compared with 256K for Kimi K2.6.
GPT-5.3 Codex is ahead on BenchLM's provisional leaderboard, 86 to 85. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 77.3% and 66.7%.
Kimi K2.6 has the edge for coding in this comparison, averaging 72 versus 63.1. Inside this category, Vibe Code Bench is the benchmark that creates the most daylight between them.
Kimi K2.6 has the edge for agentic tasks in this comparison, averaging 73.1 versus 71.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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