Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Pro (Max)
87
Ornith-1.0-397B
96
Verified leaderboard positions: DeepSeek V4 Pro (Max) #6 · Ornith-1.0-397B unranked
Pick Ornith-1.0-397B if you want the stronger benchmark profile. DeepSeek V4 Pro (Max) only becomes the better choice if you need the larger 1M context window.
Agentic
+3.5 difference
Coding
+6.5 difference
DeepSeek V4 Pro (Max)
Ornith-1.0-397B
$1.74 / $3.48
$0 / $0
N/A
N/A
N/A
N/A
1M
262K
Pick Ornith-1.0-397B if you want the stronger benchmark profile. DeepSeek V4 Pro (Max) only becomes the better choice if you need the larger 1M context window.
Ornith-1.0-397B is clearly ahead on the provisional aggregate, 96 to 87. 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 75.9. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 67.9% to 77.5%.
DeepSeek V4 Pro (Max) is also the more expensive model on tokens at $1.74 input / $3.48 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. DeepSeek V4 Pro (Max) gives you the larger context window at 1M, compared with 262K for Ornith-1.0-397B.
Ornith-1.0-397B is ahead on BenchLM's provisional leaderboard, 96 to 87. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 67.9% and 77.5%.
Ornith-1.0-397B has the edge for coding in this comparison, averaging 82.4 versus 75.9. Inside this category, Terminal-Bench 2.0 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 74. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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