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SQL · 4 checks · max 500 tokens · benched 2026-09-16

Grok 4.6 vs Grok 4.5 vs Grok 4.20 vs Grok 4.3 on products over 100 units with having

xAI models side by side on "Products over 100 units with HAVING": Grok 4.3 scores 10/10; Grok 4.3 is the cheapest answer scoring 8+ at $0.65 per 1,000 runs. Outputs, checks, judge reasons, latency and cost.

The prompt every model received

System

You are a database engineer. Reply with a single SQL statement and nothing else.

User

Tables: products(id, name) and order_items(product_id, quantity). Write one standard SQL query that lists product names whose total quantity sold across all order_items is greater than 100. Filter the aggregate with a HAVING clause.

Rubric for the judge: Join, SUM(quantity), GROUP BY product, HAVING > 100; returns names only; no WHERE on the aggregate.

Side by side

Every cell is one OpenRouter call at temperature 0 with the prompt's token cap and reasoning effort "low" where the model supports it. Cost is usage × the catalogue rate in models.json. Quality is one judge call to anthropic/claude-haiku-4.5 against the prompt's rubric, cached per prompt version.

Grok 4.6

x-ai/grok-4.6

10/10
Latency
369ms
Cost
$0.00164
Per 1,000
$1.64

276 in · 214 out (176 reasoning) · 20 words · checks 4/4

  • regex
  • regex
  • regex
  • regex
SELECT p.name FROM products p JOIN order_items oi ON p.id = oi.product_id GROUP BY p.id, p.name HAVING SUM(oi.quantity) > 100;

Judge: Query correctly joins products and order_items, groups by product, uses HAVING with SUM(quantity) > 100, returns only names, and contains no WHERE clause filtering the aggregate.

Grok 4.5

x-ai/grok-4.5

10/10
Latency
218ms
Cost
$0.00128
Per 1,000
$1.28

276 in · 158 out (123 reasoning) · 19 words · checks 4/4

  • regex
  • regex
  • regex
  • regex
SELECT p.name FROM products p JOIN order_items oi ON p.id = oi.product_id GROUP BY p.name HAVING SUM(oi.quantity) > 100;

Judge: Query correctly joins tables, groups by product name, uses SUM(quantity) in HAVING clause to filter aggregates > 100, returns only names, and contains no WHERE clause on the aggregate.

Grok 4.20

x-ai/grok-4.20

10/10
Latency
377ms
Cost
$0.00100
Per 1,000
$1.00

252 in · 327 out (295 reasoning) · 19 words · checks 4/4

  • regex
  • regex
  • regex
  • regex
SELECT p.name FROM products p JOIN order_items oi ON p.id = oi.product_id GROUP BY p.name HAVING SUM(oi.quantity) > 100;

Judge: Query correctly joins tables, groups by product name, uses SUM(quantity) in HAVING clause to filter aggregates > 100, returns only names, and contains no WHERE clause on the aggregate.

Grok 4.3

x-ai/grok-4.3

10/10
top judge scorecheapest scoring 8+
Latency
384ms
Cost
$0.00065
Per 1,000
$0.65

258 in · 210 out (178 reasoning) · 19 words · checks 4/4

  • regex
  • regex
  • regex
  • regex
SELECT p.name FROM products p JOIN order_items oi ON p.id = oi.product_id GROUP BY p.name HAVING SUM(oi.quantity) > 100;

Judge: Query correctly joins tables, groups by product name, uses SUM(quantity) in HAVING clause to filter aggregates > 100, returns only names, and contains no WHERE clause on the aggregate.

Frequently asked

What does this prompt test?

SQL: Join, SUM(quantity), GROUP BY product, HAVING > 100; returns names only; no WHERE on the aggregate. The deterministic checks are regex, regex, regex, regex.

Which model should I pick for this task?

If the judge's bar of 8/10 is good enough for you, Grok 4.3 at $0.65 per 1,000 runs. If you need the top score, Grok 4.3 at $0.65 per 1,000 runs.

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