ui/paloozadesign lab

Stats.

Runtime, tokens, and turns across models and coding agents.

Published snapshot
Samples
Skills

1818 latest finished attempts · 41 not published · Median per run · Available coverage; not matched across models

Within each column Lowest Highest Less time / fewer tokens or turns → more. Ties and missing values stay neutral.

Model overview

Click a model to inspect the underlying runs.

Stats by model and coding agent
Model / agent Finished runs Not published
Muse Spark OpenPi · Lunaroute1m 35s128 measured321.8K128 measured14128 measured16128 measured1280
Muse Wonder 1.0Pi · Lunaroute1m 44s24 measured164K24 measured1024 measured9.524 measured248
BeamPi · Lunaroute2m 21s76 measured388.7K76 measured2276 measured2276 measured7610
GPT-6 LunaCodex2m 48s111 measured335.7K111 measured12111 measured11111 measured1111
Claude Sonnet 5.5Claude Code3m 23s128 measured379.2K128 measured12128 measured16.5128 measured1280
Claude Haiku 5.5Claude Code3m 55s51 measured434.6K51 measured1151 measured1651 measured511
DeepSeek 4.1 Flash · BasePi · Lunaroute4m 26s128 measured1.5M128 measured31128 measured37128 measured1280
Muse Spark 1.3Pi · Lunaroute4m 36s128 measured352.3K128 measured16128 measured16128 measured1280
GLM 5.3 FlashPi · Lunaroute4m 39s128 measured988.4K128 measured28.5128 measured33128 measured1280
GPT-6 SolCodex5m 34s111 measured536K111 measured16111 measured15111 measured1111
GPT-5.6 SolCodex5m 46s111 measured664.4K111 measured19111 measured18111 measured1113
GLM 5.2Pi · Lunaroute6m 53s128 measured845.2K128 measured29128 measured30128 measured1289
Claude Opus 5.5Claude Code7m 44s41 measured622.3K41 measured1441 measured2641 measured412
DeepSeek 4.1 Flash · 1017Pi · Lunaroute9m 01s128 measured3.5M128 measured48.5128 measured54128 measured1280
Claude Sonnet 5Claude Code10m 12s128 measured2.2M128 measured34128 measured43128 measured1280
GPT-6 AstraCodex10m 31s107 measured408.4K107 measured12107 measured11107 measured1072
GLM 5.3Pi · Lunaroute12m 15s128 measured1.4M128 measured32128 measured37128 measured1280
Claude Opus 5Claude Code17m 40s34 measured4.5M34 measured5534 measured61.534 measured344

Counts matter: models with different coverage are not a matched comparison. Use Shared cells for the same brief × version × skill × sample across every displayed model.

Model × skill

Each cell aggregates the selected briefs and samples.

Stats by model and skill
How these numbers are calculated

Generation time is the recorded generation duration, including agent setup where the runner includes it. It excludes screenshot capture, evaluation, and priority queue wait. Total elapsed time includes capture and evaluation. Missing measurements appear as a dash, never an inferred zero.

Reported tokens uses the runner’s recorded total, summed over its responses. It includes reused context, not just newly written code. Codex input includes cached input; Claude and Pi expose cache read/write separately. We do not add cache counters to reported totals again. Tokenizers and accounting differ; this is usage, not a price comparison. Output tokens are available in the matrix and run details. Zero means the runner recorded zero, which can happen before a provider error.

Turns means assistant responses in Pi, completed model responses in Codex, and unique assistant messages/native turn counts in Claude Code. A tool call is separate, and agents can make several per turn. Tool calls and turns are not interchangeable across agents.

Latest per cell chooses the latest attempt before filtering outcomes. Unpublished attempts are included by default and counted separately. Partial evaluator results remain included under “Completed generation.” All attempts includes retries. Median/mean give each included run equal weight; totals reflect the selected coverage. Live and queued runs are excluded from aggregates. No design quality ranking is implied.

A test of taste.

Give different AI models the same brief. What do they choose for the type, the layout, the way an interface works?

UI Palooza puts those choices side by side. Compare models, add a design skill, or look across attempts to see what changes and what keeps showing up.

The story behind UI Palooza

Underlying runs

Brief / sample / skill Status Generation Elapsed Tokens Output Turns Links
YOUR BRIEF. THEIR TASTE.

What would they make
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