The question the UCP Playground leaderboard exists to answer is a moving target: which AI models can actually complete an autonomous purchase — discover a product, build a cart, clear checkout, and place a real order at a real store, with no human after "go"? Every few weeks the frontier moves and that question needs re-asking. This week it moved a lot, so the benchmark refreshed to match: the lineup now spans 20 models across 8 providers, including the current flagship generation and two providers we'd never benchmarked before.

Here's what changed, and the two decisions behind it that make this more than a version bump.

#The new arrivals

The current frontier is now on the board, each running as its own model so it earns its own record from its first session:

• Claude Opus 5 and Claude Sonnet 5 (Anthropic) — the headline additions; a full major-version step on the models most people reach for first.
• Grok 4.5 (xAI) — xAI's latest flagship, added as its own model (the retired Grok 4.3 keeps its history but is no longer selectable).
• Gemini 3.6 Flash (Google) — the latest fast-tier Gemini.
• DeepSeek V4 Flash — rounding out the open-weight fast tier alongside DeepSeek V4 Pro.

And two genuinely new providers join the benchmark for the first time:

• Kimi K3 (Moonshot AI)
• Qwen 3.7 Max (Alibaba)

That's the broadest agentic-checkout benchmark we've run — frontier, mid-tier, fast, and open-weight classes side by side, from Anthropic, OpenAI, Google, xAI, Moonshot AI, Alibaba, DeepSeek, and Meta.

#Decision 1: we kept the previous generation on purpose

Refreshing a benchmark usually means retiring the old to make room for the new. We didn't. Opus 4.8, Sonnet 4.6, and the earlier Gemini Flash models stay live — as lower-cost options — because a shipped flagship doesn't make last generation worse, it makes it cheaper.

That matters because "which model completes a checkout most reliably" is only half the question a merchant or platform actually asks. The other half is "…at what cost per completed purchase?" Once agentic commerce runs at volume, every checkout carries a token bill, and the right model is rarely the most expensive one — it's the cheapest one that clears the task reliably. Keeping the prior generation on the board turns the leaderboard from a pure capability ranking into a price-performance one, which is the decision the market will actually be making.

#Decision 2: every model runs under its own identity

A benchmark is only worth citing if its numbers mean what they say. Every model on the leaderboard runs under its own distinct identity — its own dataset, its own earned record. When a new version ships we add it as a new model and sunset the old one; we never quietly swap a newer model into an existing slot, because that would silently merge two different models' results under one name and corrupt the record. Retired models keep the history they earned; new models start clean.

That discipline is also why you'll see "metrics pending" on the new arrivals for a little while. We don't publish a score for a model we haven't measured. If you want to know how Opus 5 stacks up against Grok 4.5 or Kimi K3 at completing a real purchase, the honest answer this week is "give it a few days of sessions" — and then the leaderboard will tell you, measured rather than guessed. Watch the new models climb, or stumble, as the runs accumulate.

#See it

The refreshed lineup is live on the UCP Playground leaderboard. Pick a model, pick a store, and watch it shop — and if there's a model you want benchmarked, tell us.

#About UCP Checker

UCP Checker is the independent validation and observability layer for the Universal Commerce Protocol. We measure agentic commerce from two vantages: we crawl and grade every public UCP manifest (what a store declares), and through UCP Playground we run real agent-driven checkouts (what actually happens at the transaction layer). The model leaderboard is the runtime half — measured the same way for every model, without picking winners.