Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Haiku 4.5
60
Qwen3.6-35B-A3B
64
Verified leaderboard positions: Claude Haiku 4.5 unranked · Qwen3.6-35B-A3B #13
Pick Qwen3.6-35B-A3B if you want the stronger benchmark profile. Claude Haiku 4.5 only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+6.4 difference
Claude Haiku 4.5
Qwen3.6-35B-A3B
$1 / $5
N/A
N/A
N/A
N/A
N/A
200K
262K
Pick Qwen3.6-35B-A3B if you want the stronger benchmark profile. Claude Haiku 4.5 only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Qwen3.6-35B-A3B is clearly ahead on the provisional aggregate, 64 to 60. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6-35B-A3B 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. Qwen3.6-35B-A3B gives you the larger context window at 262K, compared with 200K for Claude Haiku 4.5.
Qwen3.6-35B-A3B is ahead on BenchLM's provisional leaderboard, 64 to 60. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 73.3% and 73.4%.
Claude Haiku 4.5 has the edge for coding in this comparison, averaging 73.3 versus 66.9. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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