Independent evaluation of Haiku 5.5 scores 43 points, far outperforming GPT-6 Luna, though its highest-tier token consumption is over three times higher.

Beating AI News – Third-party evaluation firm Artificial Analysis has released test results for Claude Haiku 5.5. The new model scored 43 points in the General Intelligence Index, a 26-point improvement over the previous generation’s 17 points. It outperformed GPT-6 Luna (38 points) and GLM-5.3 Flash (42 points), and is close to Kimi K3 (44 points). The index integrates 10 tests including programming, professional work, and scientific reasoning. However, the high score comes with substantial token consumption. At maximum inference intensity, Haiku 5.5 outputs an average of ~162,000 tokens per evaluation task, 3.2 times that of GPT-6 Luna. Both models have the same base API unit price, but Haiku 5.5’s estimated per-task cost is ~$0.21, compared to Luna’s $0.07. When adjusted from the second-highest tier to the maximum tier, Haiku 5.5’s overall score only rises by 2 points, while its output volume increases by ~80%. Reducing inference intensity narrows the gap significantly: Haiku 5.5 scores 38 points at the high tier, with an average of ~55,000 tokens per task, matching GPT-6 Luna’s 38 points and 50,000 tokens at the maximum tier. Developers can adjust inference intensity to cut unnecessary token consumption. Haiku 5.5 is not fully superior, though. In the AutomationBench-AA automation task evaluation, it scored only 35%, lagging behind Luna’s 53%. However, the model had an issue of over-refusing tasks during testing; Anthropic is addressing this, and Artificial Analysis plans to retest. Additionally, the currently disclosed task cost for Haiku 5.5 does not include long context surcharges, so actual fees may be higher.