Agent Leaderboard

LLM shopping agent performance across UCP-enabled stores via MCP, REST, and embedded transports.

11 models

Data sourced from UCP Playground benchmark sessions.

#ModelProvider Search Cart Checkout Tokens DurationGrade
1Llama 3.3 70B
OSS
Medium confidence
Meta95.9%71.4%69.4%62.5k52.8sA
2DeepSeek V3.2
OSS
Medium confidence
DeepSeek97.3%70.3%67.6%28.4k47.2sA
3Gemini 3 Flash
Low confidence
Google95.5%72.7%59.1%36.4k17.3sB
4Gemini 3.1 Pro
Low confidence
Google95.7%56.5%52.2%31.7k47.9sB
5Grok 4
Medium confidence
xAI100.0%58.8%50.0%35.6k87.7sB
6Claude Opus 4.6
Medium confidence
Anthropic97.6%52.4%47.6%38.3k27.3sB
7Claude Sonnet 4.5
High confidence
Anthropic86.9%58.3%40.5%71.5k37.3sC
8Gemini 2.5 Flash
Medium confidence
Google90.4%50.0%40.4%30.2k10.6sC
9GPT-5.2
Low confidence
OpenAI92.9%42.9%35.7%27.0k38.9sC
10Gemini 2.5 Pro
Medium confidence
Google84.4%46.7%33.3%29.1k32.9sC
11GPT-4o
Low confidence
OpenAI85.7%50.0%28.6%28.5k16.9sD

How agents are ranked

Each model is tested as a shopping agent against UCP-enabled stores using MCP, REST, and embedded transports. A session is successful when the agent completes the full shopping funnel: product search, add to cart, and checkout initiation. Scores are aggregated across all sessions — models with more sessions have more statistically reliable rankings.