Tech • AI • Robotics • Game
Claude Haiku 5.5 is SUPER SMART (I can’t believe my eyes)
7/10TL;DR
IQ 5.5 is positioned as a low-cost, fast small model that is especially useful for sub-agents, UI generation and lightweight coding tasks, though stronger models still lead on raw reasoning.
KEY POINTS
Positioning as a small, efficient model
IQ 5.5 is framed not as a frontier model but as a practical model optimized for speed, price and acceptable capability. It is presented as the cheapest, fastest and most capable small model in its class, with the clearest gains over IQ 4.5 in computer-use tasks and a more competitive level in coding.
Major improvement over IQ 4.5
Benchmark comparisons point to a substantial jump from IQ 4.5 to IQ 5.5, especially in reasoning modes. One cited comparison shows IQ 4.5 scoring 17 versus 29 for IQ 5.5 L, suggesting a notable leap for users who want better performance without moving to premium large models.
Pricing favors short, specialized jobs
Pricing is listed at $0.10 per 100,000 input tokens and $0.50 per 100,000 output tokens for the first tier, then rising by 5x beyond that threshold. That structure makes the model particularly attractive for specialized sub-agents that work on narrow tasks and avoid long token-heavy runs.
Sub-agent orchestration is a core use case
A highlighted test compared a single high-end agent with a setup using 10 IQ sub-agents managed by a stronger model. The multi-agent version completed the task in 58 seconds, tested 81 designs, and cost $0.14, versus 3 minutes 37 seconds, 25 designs, and $0.47 for the single-agent approach. The result suggests IQ 5.5 can be highly effective when deployed in parallel for exploration and iteration.
Cost-per-intelligence looks competitive
In comparisons focused on cost per intelligence, IQ 5.5 Medium and IQ 5.5 Low were presented as among the most attractive points on the curve. More expensive families still win in absolute capability, but IQ 5.5 appears to offer a strong trade-off for teams optimizing budget and throughput rather than chasing the highest benchmark score.
Raw intelligence still trails stronger models
Tests indicate that Opus 5.5 and other larger models remain clearly ahead in top-end reasoning. One direct comparison found that Opus 5.5 Low could outperform IQ 5.5 Extra High while also responding faster, reinforcing that IQ 5.5 is not the best choice when the hardest reasoning tasks matter most.
Mixed results in autonomous coding tests
In a vehicle simulation task, IQ 5.5 struggled, with one run taking 19 minutes and producing a car that broke or spun in circles. By contrast, GPT-6 Luna Extra High produced a more workable result for roughly 0.5 cents, while medium modes across several models often failed outright. The pattern suggests that small models can be erratic in open-ended autonomous coding.
UI generation is a standout strength
The most striking results came from interface work. In a Gmail clone task, IQ 5.5 delivered near-Google-quality UI detail for about 1 cent, compared with around $1.65 and 58 minutes for a stronger competitor in one comparison. Another generated interface reportedly cost 0.02 cents, reinforcing the model’s reputation for producing polished front-end layouts at extremely low cost.
Visual and simulation demos showed strong design instincts
In creative coding tests such as a lava-lamp simulation, IQ 5.5 Extra High reportedly produced impressive interactive visuals for about 2 cents, using 2 million input tokens and 271,000 output tokens. A separate video-generation-style task was completed in 33 minutes for around 1 cent, again showing that the model’s strongest edge may be design-heavy implementation rather than deep reasoning.
CONCLUSION
IQ 5.5 appears to fill a clear niche: a fast, inexpensive model for sub-agents, UI work and parallel task execution. It does not replace top-tier reasoning models, but it offers a compelling economics-first option for high-volume workflows.
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