Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Flash (High)
71
Laguna M.1
46
Verified leaderboard positions: DeepSeek V4 Flash (High) #19 · Laguna M.1 unranked
Pick DeepSeek V4 Flash (High) if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if you want the cheaper token bill.
Agentic
+14.7 difference
Coding
+15.8 difference
DeepSeek V4 Flash (High)
Laguna M.1
$0.14 / $0.28
$0 / $0
N/A
N/A
N/A
N/A
1M
131K
Pick DeepSeek V4 Flash (High) if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if you want the cheaper token bill.
DeepSeek V4 Flash (High) is clearly ahead on the provisional aggregate, 71 to 46. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V4 Flash (High)'s sharpest advantage is in coding, where it averages 72.2 against 56.4. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 56.6% to 40.7%.
DeepSeek V4 Flash (High) is also the more expensive model on tokens at $0.14 input / $0.28 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Laguna M.1. That is roughly Infinityx on output cost alone. DeepSeek V4 Flash (High) gives you the larger context window at 1M, compared with 131K for Laguna M.1.
DeepSeek V4 Flash (High) is ahead on BenchLM's provisional leaderboard, 71 to 46. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 56.6% and 40.7%.
DeepSeek V4 Flash (High) has the edge for coding in this comparison, averaging 72.2 versus 56.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
DeepSeek V4 Flash (High) has the edge for agentic tasks in this comparison, averaging 55.4 versus 40.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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