CommerceAgentBench
Agents finish real e-commerce work across procurement, listings, operations, fulfillment and after-sales through CLI, browser, file and API tools. A task passes only if every verifier check on the end state succeeds.
107 tasks: 53 CLI, 28 browser, 16 file and 10 API or MCP. Tasks were distilled from Accio merchant traces. Verifiers are deterministic or LLM-assisted per task. Formerly RealReplicaBench. Repo has 1,301 stars.
- Made by
- Alibaba.com (Accio)
- Released
- August 2026
- Kind
- Running a business
- Level
- Expert
- Scored
- Checked automatically
- Answers
- Agent task
- Tasks
- All public
- Strongest model tested
- Claude Opus 5 #10 on the capability index
- Last model added
- August 2026
- Scores refreshed
- November 12th, 2026
Claude Opus 5 leads with 61.7% among models released by August 2026
Best score per model from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Every run is in the next chart.
The newest model with a score here came out in August 2026, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- Claude Fable 5.2
-
Gemini 4 Carbon
- GPT-6 Astra
- Claude Opus 5.5
- and 13 more
- 1 Claude Opus 5 61.7%
- 2 Claude Opus 4.8 55.1%
- 3 Claude Opus 4.7 52.3%
- 4
Qwen 3.8 Max 52.3%
- 5 GPT-5.6 Sol 51.4%
- 6
DeepSeek-V4-Pro 50.5%
- 7 GPT-5.5 47.7%
- 8
DeepSeek-V4-Flash 46.7%
- 9 GLM-5.2 46.7%
- 10
Gemini 3.6 Flash 46.7%
- 11 GPT-5.6 Luna 44.9%
- 12
Gemini 3.5 Flash 43%
- 13
Gemini 3 Flash 29%
Source: Official CommerceAgentBench leaderboard
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Claude Opus 5 | 61.7% | Accio | Jul 2026 | Official leaderboard |
| 2 | Claude Opus 4.8 | 55.1% | Accio | May 2026 | Official leaderboard |
| 3 | Claude Opus 4.7 | 52.3% | Accio | Apr 2026 | Official leaderboard |
| 4 | | 52.3% | Accio | Aug 2026 | Official leaderboard |
| 5 | GPT-5.6 Sol | 51.4% | Accio | Jul 2026 | Official leaderboard |
| 6 | | 50.5% | Accio | Apr 2026 | Official leaderboard |
| 7 | GPT-5.5 | 47.7% | OpenClaw | Apr 2026 | Official leaderboard |
| 8 | | 46.7% | Accio | Apr 2026 | Official leaderboard |
| 9 | GLM-5.2 | 46.7% | Pi | Jun 2026 | Official leaderboard |
| 10 | | 46.7% | Accio | Jul 2026 | Official leaderboard |
| 11 | GPT-5.6 Luna | 44.9% | Accio | Jul 2026 | Official leaderboard |
| 12 | | 43% | Accio | May 2026 | Official leaderboard |
| 13 | | 29% | Pi | Dec 2025 | Official leaderboard |
Pass rate vs. task cost
The line joins the runs that no other run beats on both measures. We redrew this chart from the numbers on the official leaderboard.
| Model | Setting | Pass rate | Average task cost |
|---|---|---|---|
| Claude Opus 5 | Accio | 61.7% | $3.51 |
| Claude Opus 5 | Pi | 60.8% | $1.79 |
| Claude Opus 5 | OpenClaw | 56.1% | $2.7 |
| Claude Opus 4.8 | Accio | 55.1% | $4.17 |
| | Accio | 52.3% | $1.28 |
| Claude Opus 4.8 | Pi | 52.3% | $1.83 |
| Claude Opus 4.7 | Accio | 52.3% | $3.3 |
| GPT-5.6 Sol | Accio | 51.4% | $2.79 |
| Claude Opus 4.8 | OpenClaw | 51.4% | $3.57 |
| | Accio | 50.5% | $0.24 |
| | Pi | 49.5% | $0.2 |
| | Pi | 49.5% | $0.72 |
| GPT-5.6 Sol | OpenClaw | 49.5% | $3.16 |
| GPT-5.6 Sol | Pi | 48.6% | $1.08 |
| Claude Opus 4.7 | Pi | 48.6% | $1.86 |
| GPT-5.5 | OpenClaw | 47.7% | $2.73 |
| | Accio | 46.7% | $0.04 |
| GLM-5.2 | Pi | 46.7% | $0.28 |
| GLM-5.2 | Accio | 46.7% | $1.25 |
| | Accio | 46.7% | $1.35 |
| Claude Opus 4.7 | OpenClaw | 45.8% | $3.39 |
| GPT-5.6 Luna | Accio | 44.9% | $0.73 |
| GPT-5.5 | Accio | 44.9% | $2 |
| | OpenClaw | 44.9% | $2.93 |
| | OpenClaw | 43.9% | $0.31 |
| | OpenClaw | 43.9% | $0.83 |
| GPT-5.5 | Pi | 43.9% | $1.31 |
| | Pi | 43.9% | $2.03 |
| | Pi | 43% | $0.06 |
| | OpenClaw | 43% | $0.07 |
| | Accio | 43% | $2.05 |
| | Pi | 41.1% | $3.27 |
| GPT-5.6 Luna | Pi | 39.3% | $0.03 |
| GLM-5.2 | OpenClaw | 39.3% | $1.08 |
| | OpenClaw | 36.5% | $2.11 |
| GPT-5.6 Luna | OpenClaw | 33.6% | $0.48 |
| | Accio | 29% | $0.38 |
| | OpenClaw | 29% | $0.51 |
| | Pi | 29% | $0.61 |
The best score, 61.7%, costs $3.50 a task
Runs on the cost frontier score higher than any run that's cheaper. The costs are the leaderboard's own estimates, so compare them only within this benchmark.
Source: Official CommerceAgentBench leaderboard
| Model | Effort | Harness | Score | Cost per task | Output tokens |
|---|---|---|---|---|---|
| Claude Opus 5 | Accio | 61.7% | $3.50 | ||
| Claude Opus 5 | Pi | 60.8% | $1.79 | ||
| Claude Opus 5 | OpenClaw | 56.1% | $2.70 | ||
| Claude Opus 4.8 | Accio | 55.1% | $4.17 | ||
| Claude Opus 4.7 | Accio | 52.3% | $3.30 | ||
| Claude Opus 4.8 | Pi | 52.3% | $1.83 | ||
| | Accio | 52.3% | $1.28 | ||
| Claude Opus 4.8 | OpenClaw | 51.4% | $3.57 | ||
| GPT-5.6 Sol | Accio | 51.4% | $2.79 | ||
| | Accio | 50.5% | $0.24 | ||
| | Pi | 49.5% | $0.20 | ||
| GPT-5.6 Sol | OpenClaw | 49.5% | $3.16 | ||
| | Pi | 49.5% | $0.72 | ||
| Claude Opus 4.7 | Pi | 48.6% | $1.86 | ||
| GPT-5.6 Sol | Pi | 48.6% | $1.08 | ||
| GPT-5.5 | OpenClaw | 47.7% | $2.73 | ||
| | Accio | 46.7% | $0.04 | ||
| GLM-5.2 | Pi | 46.7% | $0.28 | ||
| GLM-5.2 | Accio | 46.7% | $1.25 | ||
| | Accio | 46.7% | $1.34 | ||
| Claude Opus 4.7 | OpenClaw | 45.8% | $3.39 | ||
| GPT-5.5 | Accio | 44.9% | $2.00 | ||
| GPT-5.6 Luna | Accio | 44.9% | $0.73 | ||
| | OpenClaw | 44.9% | $2.92 | ||
| GPT-5.5 | Pi | 43.9% | $1.31 | ||
| | OpenClaw | 43.9% | $0.31 | ||
| | Pi | 43.9% | $2.03 | ||
| | OpenClaw | 43.9% | $0.83 | ||
| | Pi | 43% | $0.06 | ||
| | OpenClaw | 43% | $0.07 | ||
| | Accio | 43% | $2.05 | ||
| | Pi | 41.1% | $3.27 | ||
| GLM-5.2 | OpenClaw | 39.3% | $1.07 | ||
| GPT-5.6 Luna | Pi | 39.3% | $0.03 | ||
| | OpenClaw | 36.5% | $2.11 | ||
| GPT-5.6 Luna | OpenClaw | 33.6% | $0.48 | ||
| | Pi | 29% | $0.61 | ||
| | OpenClaw | 29% | $0.51 | ||
| | Accio | 29% | $0.38 |
Number one over time
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Official CommerceAgentBench leaderboard
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Official CommerceAgentBench leaderboard
No lab model card reports it yet
We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark.
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