Agent shopping sessions, observed.
UCP Playground runs real AI models against real UCP-verified stores and logs every JSON-RPC tool call. The aggregate across 16 models from 7 vendors and 203 stores tells us what works in agentic shopping — and what doesn't.
Pick a model. Pick a UCP-verified store. The agent connects to the store's MCP endpoint, browses, carts, and tries to check out — using only the tools the store advertises in its /.well-known/ucp manifest.
Every JSON-RPC request and response, every retry, every failed schema match — captured per session. Postman for agentic commerce: inspect what an agent actually did, not what it claimed to do.
Models from Anthropic, Google, OpenAI, Meta, DeepSeek, xAI, Alibaba run side-by-side against the same stores. Vendors can't credibly benchmark themselves; the platform layer has the same problem one level down.
Roughly 1 in 5 sessions. Highest checkout completion among frontier models. Fast, decisive tool-call rhythm — not deliberation.
DeepSeek R1, QwQ, Grok 3 Mini consistently burn tokens on chain-of-thought and miss the next tool call. Agentic shopping rewards speed, not introspection.
A well-typed manifest and tight tool responses move the conversion needle more than swapping models. Most "the agent is broken" tickets are actually store-side.
| Model | Avg tokens | Avg duration | Session share |
|---|---|---|---|
| Claude Sonnet 4.5 | 73,849 | 36.7s | 17.4% |
| Gemini 3 Flash | 64,214 | 19.2s | 15.3% |
| Claude Opus 4.6 | 50,874 | 30.9s | 12.9% |
| Gemini 2.5 Flash | 32,602 | 13.2s | 9.2% |
| Gemini 3.1 Pro | 52,996 | 46.7s | 7.1% |
| GPT-4o | 35,170 | 19.6s | 6.6% |
| GPT-5.2 | 65,785 | 42.1s | 6.4% |
| Llama 3.3 70B | 53,656 | 40.7s | 5.2% |
| Gemini 2.5 Pro | 33,690 | 33.5s | 5.1% |
| DeepSeek v3.2 | 46,784 | 50.7s | 4% |
| Grok 4 | 26,464 | 61.1s | 3.8% |
| o4-mini | 69,653 | 36.7s | 2% |
| QwQ 32B | 16,557 | 41.6s | 2% |
| Grok 3 Mini | 44,539 | 50.6s | 1.9% |
| DeepSeek R1 | 28,052 | 57.1s | 1.2% |
| Tool | Call share | Avg latency | Error rate |
|---|---|---|---|
| search_catalog | 25.1% | 902ms | 18.9% |
| search_shop_catalog | 23.2% | 482ms | 19.9% |
| update_cart | 18.9% | 586ms | 31.6% |
| search_global_products | 12.6% | 347ms | 0% |
| get_product_details | 9.1% | 273ms | 17.4% |
| get_cart | 3% | 211ms | 51% |
| search_shop_policies_and_faqs | 2.5% | 2,207ms | 19.5% |
| ucp_list_products | 2.3% | 1,670ms | 2.7% |
| create_checkout | 1.9% | 1,053ms | 48.4% |
| get_product | 1.4% | 789ms | 30.4% |
Common questions
What is UCP Playground?
How is UCP Playground different from UCP Checker?
Is UCP Playground a UCP demo?
demo-travel.ucp.dev, sandbox subdomains) so you can watch UCP in action without affecting production inventory.Which AI model performs best at agentic shopping?
Why do reasoning-tuned models underperform on shopping tasks?
How is the checkout completion rate calculated?
How many stores has UCP Playground tested?
Does my store implementation matter more than the model I pick?
Is UCP Playground free to use?
How do I run a UCP test on my own store?
/.well-known/ucp manifest and reachable MCP or REST endpoints, agent sessions will run against it directly. Stores that grade well on UCP Score typically also pass UCP tests in Playground, but a Playground test surfaces runtime issues that static checks cannot — schema drift, slow tool responses, partial cart state, missing variant data.How is the data on this page refreshed?
Run your own agent session
Pick a model, pick a store, watch the agent shop. Every JSON-RPC tool call is logged and every session is replayable — so you can see what an agent actually did, not just what it claimed.
Open UCP PlaygroundBuilding your own agent? Start at /agents · Reading the spec? /protocol
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