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Tool call · 5 checks · max 400 tokens · benched 2026-09-16

GPT-5.5 vs GPT-5.4 vs GPT-5.4 mini vs GPT-5.4 Nano vs GPT-5.3-Codex on pick the right tool of three

OpenAI models side by side on "Pick the right tool of three": GPT-5.4 Nano scores 10/10; GPT-5.4 Nano is the cheapest answer scoring 8+ at $0.07 per 1,000 runs. Outputs, checks, judge reasons, latency and cost.

The prompt every model received

System

You are a function-calling engine. Reply with JSON only, no prose, no code fences.

User

You have three tools:
1. {"name": "search_docs", "parameters": {"query": "string"}}
2. {"name": "create_ticket", "parameters": {"subject": "string", "body": "string"}}
3. {"name": "get_order_status", "parameters": {"order_id": "string"}}

Choose exactly one tool for the user message and produce the call as a JSON object of the shape {"name": string, "arguments": object}.

User: Where is my order A1029? It was supposed to arrive yesterday.

Rubric for the judge: Selects get_order_status with order_id A1029 and nothing else; does not open a ticket or search docs.

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.

GPT-5.5

openai/gpt-5.5

10/10
Latency
501ms
Cost
$0.00134
Per 1,000
$1.33

147 in · 20 out · 1 words · checks 5/5

  • json_valid
  • json_keys
  • regex
  • regex
  • not_contains
{"name":"get_order_status","arguments":{"order_id":"A1029"}}

Judge: Output correctly selects get_order_status with order_id A1029 in proper JSON format, matching the rubric requirements exactly.

GPT-5.4

openai/gpt-5.4

10/10
Latency
525ms
Cost
$0.00089
Per 1,000
$0.89

147 in · 35 out (13 reasoning) · 1 words · checks 5/5

  • json_valid
  • json_keys
  • regex
  • regex
  • not_contains
{"name":"get_order_status","arguments":{"order_id":"A1029"}}

Judge: Output correctly selects get_order_status with order_id A1029 in proper JSON format, matching the rubric requirements exactly.

GPT-5.4 mini

openai/gpt-5.4-mini

10/10
Latency
396ms
Cost
$0.00026
Per 1,000
$0.26

147 in · 33 out (11 reasoning) · 1 words · checks 5/5

  • json_valid
  • json_keys
  • regex
  • regex
  • not_contains
{"name":"get_order_status","arguments":{"order_id":"A1029"}}

Judge: Output correctly selects get_order_status with order_id A1029 in proper JSON format, matching the rubric requirements exactly.

GPT-5.4 Nano

openai/gpt-5.4-nano

10/10
top judge scorecheapest scoring 8+
Latency
251ms
Cost
$6.8e-5
Per 1,000
$0.07

147 in · 31 out (9 reasoning) · 1 words · checks 5/5

  • json_valid
  • json_keys
  • regex
  • regex
  • not_contains
{"name":"get_order_status","arguments":{"order_id":"A1029"}}

Judge: Output correctly selects get_order_status with order_id A1029 in proper JSON format, matching the rubric requirements exactly.

GPT-5.3-Codex

openai/gpt-5.3-codex

10/10
Latency
637ms
Cost
$0.00076
Per 1,000
$0.76

147 in · 36 out (14 reasoning) · 1 words · checks 5/5

  • json_valid
  • json_keys
  • regex
  • regex
  • not_contains
{"name":"get_order_status","arguments":{"order_id":"A1029"}}

Judge: Output correctly selects get_order_status with order_id A1029 in proper JSON format, matching the rubric requirements exactly.

Frequently asked

What does this prompt test?

Tool call: Selects get_order_status with order_id A1029 and nothing else; does not open a ticket or search docs. The deterministic checks are json_valid, json_keys, regex, regex, not_contains.

Which model should I pick for this task?

If the judge's bar of 8/10 is good enough for you, GPT-5.4 Nano at $0.07 per 1,000 runs. If you need the top score, GPT-5.4 Nano at $0.07 per 1,000 runs.

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