Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.3 Codex
85
Ornith-1.0-397B
96
Pick Ornith-1.0-397B if you want the stronger benchmark profile. GPT-5.3 Codex only becomes the better choice if you need the larger 400K context window.
Agentic
+6.0 difference
Coding
+19.3 difference
GPT-5.3 Codex
Ornith-1.0-397B
$1.75 / $14
$0 / $0
79 t/s
N/A
88.26s
N/A
400K
262K
Pick Ornith-1.0-397B if you want the stronger benchmark profile. GPT-5.3 Codex only becomes the better choice if you need the larger 400K context window.
Ornith-1.0-397B is clearly ahead on the provisional aggregate, 96 to 85. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Ornith-1.0-397B's sharpest advantage is in coding, where it averages 82.4 against 63.1. The single biggest benchmark swing on the page is SWE-bench Verified, 85% to 82.4%.
GPT-5.3 Codex is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ornith-1.0-397B. That is roughly Infinityx on output cost alone. GPT-5.3 Codex gives you the larger context window at 400K, compared with 262K for Ornith-1.0-397B.
Ornith-1.0-397B is ahead on BenchLM's provisional leaderboard, 96 to 85. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 85% and 82.4%.
Ornith-1.0-397B has the edge for coding in this comparison, averaging 82.4 versus 63.1. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Ornith-1.0-397B has the edge for agentic tasks in this comparison, averaging 77.5 versus 71.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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