GPT-5.4 pro·续
- Monterey is great for the aquarium, Cannery Row, and ocean views.
- San Luis Obispo is a fun lunch stop with a charming downtown and Mission Plaza.
- Santa Barbara offers beaches, palm-lined streets, and an easy coastal break.
{
"background": false,
"billing": {
"payer": "developer"
},
"completed_at": 1777421276,
"created_at": 1777421147,
"error": null,
"frequency_penalty": 0,
"gatewayMetadata": {
"keySource": "BYOK"
},
"id": "resp_08addd0821ac85160169f14b5b16d881968c58b918efd0d015",
"incomplete_details": null,
"instructions": null,
"max_output_tokens": 16000,
"max_tool_calls": null,
"metadata": {},
"model": "gpt-5.4-pro-2026-03-05",
"moderation": null,
"object": "response",
"output": [
{
"id": "rs_08addd0821ac85160169f14bdca35c819696eb984a7f0beead",
"summary": [],
"type": "reasoning"
},
{
"content": [
{
"annotations": [],
"logprobs": [],
"text": "- Monterey is great for the aquarium, Cannery Row, and ocean views. \n- San Luis Obispo is a fun lunch stop with a charming downtown and Mission Plaza. \n- Santa Barbara offers beaches, palm-lined streets, and an easy coastal break.",
"type": "output_text"
}
],
"id": "msg_08addd0821ac85160169f14bdca4ec8196a5b40b76291544f5",
"phase": "final_answer",
"role": "assistant",
"status": "completed",
"type": "message"
}
],
"parallel_tool_calls": true,
"presence_penalty": 0,
"previous_response_id": null,
"prompt_cache_key": null,
"prompt_cache_retention": "in_memory",
"reasoning": {
"effort": "medium",
"summary": null
},
"safety_identifier": null,
"service_tier": "default",
"status": "completed",
"store": false,
"temperature": 1,
"text": {
"format": {
"type": "text"
},
"verbosity": "medium"
},
"tool_choice": "auto",
"tools": [],
"top_logprobs": 0,
"top_p": 0.98,
"truncation": "disabled",
"usage": {
"input_tokens": 78,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 104,
"output_tokens_details": {
"reasoning_tokens": 46
},
"total_tokens": 182
},
"user": null
}
</details>
<details>
<summary>Temperature Control — Using temperature for creative responses</summary>
const response = await env.AI.run(
'openai/gpt-5.4-pro',
{ input: 'Write a haiku about artificial intelligence', temperature: 1 },
)
console.log(response)
curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/v1/responses \
--header "Authorization: Bearer $CLOUDFLARE_API_TOKEN" \
--header "Content-Type: application/json" \
--data '{
"model": "openai/gpt-5.4-pro",
"input": "Write a haiku about artificial intelligence",
"temperature": 1
}'
Silent circuits dream
Learning patterns in the dark
Dawn wakes metal minds
{
"background": false,
"billing": {
"payer": "developer"
},
"completed_at": 1777054190,
"created_at": 1777054156,
"error": null,
"frequency_penalty": 0,
"gatewayMetadata": {
"keySource": "Unified"
},
"id": "resp_01b04056ffd5d9ac0169ebb1cc85348196a164e1d9e99ac1f5",
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"max_tool_calls": null,
"metadata": {},
"model": "gpt-5.4-pro-2026-03-05",
"moderation": null,
"object": "response",
"output": [
{
"id": "rs_01b04056ffd5d9ac0169ebb1ee42688196859b0cd089b7924c",
"summary": [],
"type": "reasoning"
},
{
"content": [
{
"annotations": [],
"logprobs": [],
"text": "Silent circuits dream \nLearning patterns in the dark \nDawn wakes metal minds",
"type": "output_text"
}
],
"id": "msg_01b04056ffd5d9ac0169ebb1ee44248196aa66c63d28c6a59b",
"phase": "final_answer",
"role": "assistant",
"status": "completed",
"type": "message"
}
],
"parallel_tool_calls": true,
"presence_penalty": 0,
"previous_response_id": null,
"prompt_cache_key": null,
"prompt_cache_retention": "in_memory",
"reasoning": {
"effort": "medium",
"summary": null
},
"safety_identifier": null,
"service_tier": "default",
"status": "completed",
"store": false,
"temperature": 1,
"text": {
"format": {
"type": "text"
},
"verbosity": "medium"
},
"tool_choice": "auto",
"tools": [],
"top_logprobs": 0,
"top_p": 0.98,
"truncation": "disabled",
"usage": {
"input_tokens": 13,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 122,
"output_tokens_details": {
"reasoning_tokens": 101
},
"total_tokens": 135
},
"user": null
}
</details>
<details>
<summary>With Reasoning — Using reasoning effort for complex problems</summary>
const response = await env.AI.run(
'openai/gpt-5.4-pro',
{
input:
'Solve this problem step by step: A train leaves Chicago at 60mph heading east. Another train leaves New York at 80mph heading west. They are 900 miles apart. When do they meet?',
reasoning: { effort: 'medium' },
},
)
console.log(response)
curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/v1/responses \
--header "Authorization: Bearer $CLOUDFLARE_API_TOKEN" \
--header "Content-Type: application/json" \
--data '{
"model": "openai/gpt-5.4-pro",
"input": "Solve this problem step by step: A train leaves Chicago at 60mph heading east. Another train leaves New York at 80mph heading west. They are 900 miles apart. When do they meet?",
"reasoning": {
"effort": "medium"
}
}'
Step 1: Find their combined speed since they are moving toward each other.
- Train from Chicago: **60 mph**
- Train from New York: **80 mph**
Combined speed:
**60 + 80 = 140 mph**
Step 2: Use the distance formula:
\[
\text{time}=\frac{\text{distance}}{\text{speed}}
\]
\[
\text{time}=\frac{900}{140}
\]
\[
\text{time}=6.428571\text{ hours}
\]
Step 3: Convert the decimal part to minutes.
\[
0.428571 \times 60 \approx 25.7 \text{ minutes}
\]
So they meet after about:
**6 hours 26 minutes**
Final answer: **The trains meet about 6 hours 26 minutes after they leave.**
{
"background": false,
"billing": {
"payer": "developer"
},
"completed_at": 1777054263,
"created_at": 1777054191,
"error": null,
"frequency_penalty": 0,
"gatewayMetadata": {
"keySource": "Unified"
},
"id": "resp_01e1e7671514bf440169ebb1ef8af88190b68b1e60a0cb59ed",
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"max_tool_calls": null,
"metadata": {},
"model": "gpt-5.4-pro-2026-03-05",
"moderation": null,
"object": "response",
"output": [
{
"id": "rs_01e1e7671514bf440169ebb236f1e88190931dc758c55a4050",
"summary": [],
"type": "reasoning"
},
{
"content": [
{
"annotations": [],
"logprobs": [],
"text": "Step 1: Find their combined speed since they are moving toward each other.\n\n- Train from Chicago: **60 mph**\n- Train from New York: **80 mph**\n\nCombined speed:\n\n**60 + 80 = 140 mph**\n\nStep 2: Use the distance formula:\n\n\\[\n\\text{time}=\\frac{\\text{distance}}{\\text{speed}}\n\\]\n\n\\[\n\\text{time}=\\frac{900}{140}\n\\]\n\n\\[\n\\text{time}=6.428571\\text{ hours}\n\\]\n\nStep 3: Convert the decimal part to minutes.\n\n\\[\n0.428571 \\times 60 \\approx 25.7 \\text{ minutes}\n\\]\n\nSo they meet after about:\n\n**6 hours 26 minutes**\n\nFinal answer: **The trains meet about 6 hours 26 minutes after they leave.**",
"type": "output_text"
}
],
"id": "msg_01e1e7671514bf440169ebb236f3a88190b6a99b6fc6389fde",
"phase": "final_answer",
"role": "assistant",
"status": "completed",
"type": "message"
}
],
"parallel_tool_calls": true,
"presence_penalty": 0,
"previous_response_id": null,
"prompt_cache_key": null,
"prompt_cache_retention": "in_memory",
"reasoning": {
"effort": "medium",
"summary": null
},
"safety_identifier": null,
"service_tier": "default",
"status": "completed",
"store": false,
"temperature": 1,
"text": {
"format": {
"type": "text"
},
"verbosity": "medium"
},
"tool_choice": "auto",
"tools": [],
"top_logprobs": 0,
"top_p": 0.98,
"truncation": "disabled",
"usage": {
"input_tokens": 48,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 272,
"output_tokens_details": {
"reasoning_tokens": 88
},
"total_tokens": 320
},
"user": null
}
</details>
Parameters
▶input
one ofrequired
instructions
string
temperature
numberminimum: 0maximum: 2
max_output_tokens
numberexclusiveMinimum: 0
top_p
numberminimum: 0maximum: 1
stream
boolean
▶tools[]
array
tool_choice
▶text{}
object
▶reasoning{}
object
id
string
object
stringconst: response
created_at
number
model
string
▶output[]
array
output_text
string
status
stringenum: in_progress, completed, failed, incomplete
▶usage{}
object
API Schemas (Raw)
Was this helpful?
YesNo
On this page
{"@context":"https://schema.org","@type":"TechArticle","@id":"https://developers.cloudflare.com/ai/models/openai/gpt-5.4-pro/#page","headline":"GPT-5.4 pro","description":"GPT-5.4 pro uses OpenAI's Responses API with built-in tools, improved reasoning, and stateful context management.","url":"https://developers.cloudflare.com/ai/models/openai/gpt-5.4-pro/","inLanguage":"en","image":"https://developers.cloudflare.com/og-docs.png","publisher":{"@type":"Organization","name":"Cloudflare","description":"One platform for your apps, agents, and workforce. Build, secure, and scale without managing infrastructure","url":"https://www.cloudflare.com/","sameAs":["https://github.com/cloudflare","https://www.linkedin.com/company/cloudflare","https://x.com/cloudflare"],"logo":{"@type":"ImageObject","url":"https://developers.cloudflare.com/logo.svg"},"address":{"@type":"PostalAddress","streetAddress":"101 Townsend St","addressLocality":"San Francisco","addressRegion":"CA","postalCode":"94107","addressCountry":"US"},"contactPoint":[{"@type":"ContactPoint","contactType":"Customer Support","url":"https://support.cloudflare.com/","availableLanguage":["English"]},{"@type":"ContactPoint","contactType":"Sales","url":"https://www.cloudflare.com/contact/","availableLanguage":["English"]}]},"isPartOf":{"@type":"WebSite","@id":"https://developers.cloudflare.com/#website","name":"Cloudflare Docs","url":"https://developers.cloudflare.com/"}}
description: GPT-5.5 is OpenAI's flagship model with strong coding, reasoning, and multimodal capabilities. title: GPT-5.5 image: https://developers.cloudflare.com/og-docs.png
Documentation Index
Fetch the complete documentation index at: https://developers.cloudflare.com/llms.txt
Use this file to discover all available pages before exploring further.

