Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Haiku 4.5
59
Kimi K2.5 (Reasoning)
79
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Claude Haiku 4.5 only becomes the better choice if you need the larger 200K context window or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+3.5 difference
Claude Haiku 4.5
Kimi K2.5 (Reasoning)
$1 / $5
$null / $null
N/A
N/A
N/A
N/A
200K
128K
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Claude Haiku 4.5 only becomes the better choice if you need the larger 200K context window or you would rather avoid the extra latency and token burn of a reasoning model.
Kimi K2.5 (Reasoning) is clearly ahead on the provisional aggregate, 79 to 59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5 (Reasoning)'s sharpest advantage is in coding, where it averages 76.8 against 73.3. The single biggest benchmark swing on the page is SWE-bench Verified, 73.3% to 76.8%.
Kimi K2.5 (Reasoning) is the reasoning model in the pair, while Claude Haiku 4.5 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. Claude Haiku 4.5 gives you the larger context window at 200K, compared with 128K for Kimi K2.5 (Reasoning).
Kimi K2.5 (Reasoning) is ahead on BenchLM's provisional leaderboard, 79 to 59. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 73.3% and 76.8%.
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 76.8 versus 73.3. 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.