Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1 mini
46
Laguna XS.2
32
Pick GPT-4.1 mini if you want the stronger benchmark profile. Laguna XS.2 only becomes the better choice if coding is the priority or you want the cheaper token bill.
Coding
+29.7 difference
GPT-4.1 mini
Laguna XS.2
$0.4 / $1.6
$0 / $0
80 t/s
N/A
0.76s
N/A
1M
131K
Pick GPT-4.1 mini if you want the stronger benchmark profile. Laguna XS.2 only becomes the better choice if coding is the priority or you want the cheaper token bill.
GPT-4.1 mini is clearly ahead on the provisional aggregate, 46 to 32. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1 mini is also the more expensive model on tokens at $0.40 input / $1.60 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Laguna XS.2. That is roughly Infinityx on output cost alone. Laguna XS.2 is the reasoning model in the pair, while GPT-4.1 mini is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GPT-4.1 mini gives you the larger context window at 1M, compared with 131K for Laguna XS.2.
GPT-4.1 mini is ahead on BenchLM's provisional leaderboard, 46 to 32. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 23.6% and 68.2%.
Laguna XS.2 has the edge for coding in this comparison, averaging 53.3 versus 23.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
For engineers, researchers, and the plain curious — a weekly brief on new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.