Claude Haiku 4.5 vs Qwen3.5-35B-A3B

Treat this as a split decision. Claude Haiku 4.5 makes more sense if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model; Qwen3.5-35B-A3B is the better fit if you want the cheaper token bill or you need the larger 262K context window.

Claude Haiku 4.5 and Qwen3.5-35B-A3B finish on the same provisional overall score, so this is less about a single winner and more about where the edge shows up. The provisional headline says tie; the benchmark table is where the real choice happens.

Claude Haiku 4.5 is also the more expensive model on tokens at $1.00 input / $5.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5-35B-A3B. That is roughly Infinityx on output cost alone. Qwen3.5-35B-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. Qwen3.5-35B-A3B gives you the larger context window at 262K, compared with 200K for Claude Haiku 4.5.