AI Model Benchmark

Real-world e-commerce customer service scenarios, blind evaluation by multiple AI judges

This benchmark compares ChatGPT, Claude, Gemini, and Grok on real e-commerce customer service questions. It is designed for teams choosing the best AI model for support chat, help desk automation, and AI sales-assistant workflows.

Current leader: ChatGPT 5.6 Sol with an average score of 71.7 across 45 shared questions and 540 blind evaluations.

Include retired models

45 questions evaluated 540 evaluations performed Last updated: Aug 30, 2026

Overall ranking across all snapshots

Weighted average across 4 snapshots. Models with more evaluations weigh more heavily.

Cross-snapshot weighted-average ranking; rounds column shows how many snapshots each model participated in.
#	Model	Provider	Overall Score	Rounds	Total evals
1	ChatGPT 5.6 Sol	OpenAI	71.7	1/4	45
2	ChatGPT 5.6 Luna	OpenAI	69.8	1/4	45
3	ChatGPT 5.6 Terra	OpenAI	69.7	1/4	45
4	Claude Sonnet 5	Anthropic	63.6	1/4	45
5	Gemini 3.7 Flash	Google	63.6	1/4	45
7	Grok 4.6	xAI	63.0	1/4	45
10	ChatGPT 4.1 mini	OpenAI	62.5	4/4	263
12	Claude Opus 5	Anthropic	61.2	1/4	45
13	ChatGPT 4.1	OpenAI	60.4	4/4	263
14	Grok 4.1 Fast	xAI	60.3	2/4	157
17	Claude Haiku 4.5	Anthropic	59.3	4/4	263
18	Gemini 3.1 Pro Preview	Google	57.9	3/4	137
19	Gemini 3.5 Flash-Lite	Google	56.8	1/4	45

Latest round — Aug 30, 2026

Leaderboard of AI models ranked by blind evaluation scores on shared e-commerce customer service questions.
#	Model	Provider	Overall Score	Avg Response
1	ChatGPT 5.6 Sol	OpenAI	71.7	3.5s
2	ChatGPT 5.6 Luna	OpenAI	69.8	2.8s
3	ChatGPT 5.6 Terra	OpenAI	69.7	3.2s
4	Grok 4.1 Fast	xAI	65.2	2.2s
5	Claude Haiku 4.5	Anthropic	65.1	4.0s
6	ChatGPT 4.1 mini	OpenAI	63.9	2.9s
7	Claude Sonnet 5	Anthropic	63.6	7.8s
8	Gemini 3.7 Flash	Google	63.6	10.1s
9	Grok 4.6	xAI	63.0	49.7s
10	Claude Opus 5	Anthropic	61.2	11.4s
11	ChatGPT 4.1	OpenAI	61.2	2.3s
12	Gemini 3.5 Flash-Lite	Google	56.8	1.3s

Score Breakdown

Per-criterion benchmark scores showing how each model performs on accuracy, relevance, completeness, helpfulness, tone, and conciseness.
Model	Accuracy (30%)	Relevance (20%)	Completeness (15%)	Helpfulness (15%)	Tone (10%)	Conciseness (10%)
ChatGPT 5.6 Sol	55.4	84.7	72.1	64.8	86.0	90.4
ChatGPT 5.6 Luna	52.7	81.3	71.7	62.3	88.0	88.7
ChatGPT 5.6 Terra	51.3	84.0	70.7	59.0	89.7	90.8
Grok 4.1 Fast	49.0	78.2	64.8	55.9	82.1	85.2
Claude Haiku 4.5	45.7	79.8	68.6	57.2	85.4	80.2
ChatGPT 4.1 mini	41.6	80.0	68.3	55.0	85.2	84.6
Claude Sonnet 5	40.3	77.8	72.1	58.4	85.9	77.9
Gemini 3.7 Flash	35.4	81.4	72.0	56.7	89.3	84.3
Grok 4.6	41.0	79.1	69.6	54.1	81.1	82.2
Claude Opus 5	37.4	75.4	69.8	54.1	87.8	75.4
ChatGPT 4.1	34.4	81.2	68.3	51.2	85.3	81.3
Gemini 3.5 Flash-Lite	32.8	73.4	64.7	46.4	81.3	74.4

How It Works

Real Questions

Selected from actual production customer service conversations in e-commerce.

Same Prompt

All models receive the identical system prompt, knowledge base, and question.

Blind Evaluation

Evaluators see only 'Answer A', 'Answer B' — they don't know which model wrote it.

Cross-Evaluation

Top-tier models from each provider evaluate answers. No model judges its own response.

Scoring Criteria

Each answer is scored 0-100 on six criteria with the following weights:

Accuracy 30%

Relevance 20%

Completeness 15%

Helpfulness 15%

Tone 10%

Conciseness 10%

To keep the comparison fair, public scores are calculated only from questions answered by every model included in the selected comparison set. That prevents newer or retired models from benefiting from an easier question mix.

Results over time

Each round uses a different set of questions, so trends are indicative, not a controlled comparison.

Round-by-round average scores (all models)
Model	Round 1	Round 2	Round 3	Round 4
Claude Haiku 4.5	64.3	49.1	53.5	65.1
Claude Opus 4.6	63.0	—	—	—
Claude Opus 4.7	65.0	51.1	56.4	—
Claude Opus 5	—	—	—	61.2
Claude Sonnet 4.6	66.7	54.5	61.0	—
Claude Sonnet 5	—	—	—	63.6
Gemini 3 Flash	54.2	—	—	—
Gemini 3.1 Flash-Lite	—	53.4	55.5	—
Gemini 3.1 Flash-Lite	60.2	—	—	—
Gemini 3.1 Pro Preview	61.2	51.9	53.1	—
Gemini 3.5 Flash	—	43.8	50.5	—
Gemini 3.5 Flash-Lite	—	—	—	56.8
Gemini 3.7 Flash	—	—	—	63.6
ChatGPT 4.1	63.2	57.1	57.2	61.2
ChatGPT 4.1 mini	62.6	60.8	62.7	63.9
ChatGPT 5.4	69.5	48.7	52.2	—
ChatGPT 5.4 mini	65.9	60.6	59.9	—
ChatGPT 5.5	—	53.9	58.3	—
ChatGPT 5.6 Luna	—	—	—	69.8
ChatGPT 5.6 Sol	—	—	—	71.7
ChatGPT 5.6 Terra	—	—	—	69.7
Grok 4	59.6	—	—	—
Grok 4.1 Fast	58.4	—	—	65.2
Grok 4.20	55.5	—	—	—
Grok 4.3	—	51.2	57.7	—
Grok 4.6	—	—	—	63.0

Frequently Asked Questions

This benchmark measures how well leading AI models handle real customer service tasks for online stores. It focuses on practical support quality — accuracy, helpfulness, tone, and conciseness — rather than coding, math, or generic reasoning tests.

The best model depends on your store, language mix, product complexity, and speed requirements. This page shows which models currently perform best in our blind benchmark, helping you shortlist candidates for your own live testing.

Each provider has strengths. ChatGPT models tend to be fast and widely supported. Claude models often excel at nuanced, context-heavy responses. Gemini models offer strong multilingual capabilities. Grok models provide competitive performance at lower latency. Check the leaderboard above for the latest blind comparison.

Every model receives the identical question, system prompt, and knowledge base. Their answers are then labeled anonymously (Answer A, Answer B, etc.) and scored by top-tier AI judges from each provider — OpenAI, Anthropic, Google, and xAI. No model evaluates its own response, eliminating self-evaluation bias.

Yes. The questions come from real production conversations in online stores, including Shopify, Shoptet, WooCommerce, and others. Use the leaderboard as a starting point, then test top models with your own product catalog and brand tone before going live.

Use the leaderboard as a decision aid, not as the only deciding factor. Start with the highest-ranked models, then test them on your own knowledge base, brand tone, and response speed requirements before rolling out in production.

We add new models as providers release them and periodically expand the question set with fresh real-world scenarios. When a new model is added, it is tested on the same shared questions as all existing models to keep the comparison fair.

AI Model Benchmark

Overall ranking across all snapshots

Latest round — Aug 30, 2026

Score Breakdown

How It Works

Real Questions

Same Prompt

Blind Evaluation

Cross-Evaluation

Scoring Criteria

Results over time

Frequently Asked Questions

What is this AI benchmark measuring?

Which AI model is best for customer service?

ChatGPT vs Claude vs Gemini — which is better for ecommerce support?

How does the blind evaluation work?

Can I use this benchmark to choose an AI chatbot for my Shopify or ecommerce store?

How should I use these benchmark scores?

How often is this benchmark updated?