--- title: GPT-5.4 pro description: GPT-5.4 pro uses OpenAI's Responses API with built-in tools, improved reasoning, and stateful context management. image: https://developers.cloudflare.com/dev-products-preview.png --- > Documentation Index > Fetch the complete documentation index at: https://developers.cloudflare.com/ai/llms.txt > Use this file to discover all available pages before exploring further. [Skip to content](#%5Ftop) ![OpenAI logo](https://developers.cloudflare.com/_astro/openai.BI8PEEzI.svg) # GPT-5.4 pro Text Generation • OpenAI `openai/gpt-5.4-pro` GPT-5.4 pro uses OpenAI's Responses API with built-in tools, improved reasoning, and stateful context management. | Model Info | | | -------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------- | | Context Window[ ↗](https://developers.cloudflare.com/workers-ai/glossary/) | 1,000,000 tokens | | Terms and License | [link ↗](https://openai.com/policies/) | | More information | [link ↗](https://openai.com/) | | Zero data retention | Yes | | Request formats | Responses | | Pricing | [View pricing in the Cloudflare dashboard ↗](https://dash.cloudflare.com/?to=/:account/ai/models/openai/gpt-5.4-pro) | ## Usage * [ TypeScript ](#tab-panel-1310) * [ cURL ](#tab-panel-1311) TypeScript ``` const response = await env.AI.run( 'openai/gpt-5.4-pro', { input: 'What are the three laws of thermodynamics?' },)console.log(response) ``` Terminal window ``` 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": "What are the three laws of thermodynamics?"}' ``` * [ Output ](#tab-panel-1320) * [ Raw response ](#tab-panel-1321) The **three laws of thermodynamics** usually mean: 1. **First Law — Conservation of Energy** Energy cannot be created or destroyed, only transferred or transformed. - In thermodynamics: the change in a system’s internal energy equals heat added to the system minus work done by the system. 2. **Second Law — Entropy Increases** In any natural process, the total entropy of an isolated system tends to increase. - This means energy spontaneously spreads out, and no heat engine can be 100% efficient. - Heat naturally flows from hot objects to cold ones, not the reverse without input of work. 3. **Third Law — Entropy at Absolute Zero** As temperature approaches **absolute zero** (0 K), the entropy of a perfect crystal approaches zero. - A consequence is that absolute zero cannot be reached in a finite number of steps. Small note: thermodynamics also has a **Zeroth Law**, which is often listed before these: - If system A is in thermal equilibrium with B, and B is in thermal equilibrium with C, then A is in thermal equilibrium with C. - This is the basis for the concept of **temperature**. If you want, I can also give a **one-line intuitive version** of each law. ``` { "background": false, "billing": { "payer": "developer" }, "completed_at": 1777054203, "created_at": 1777054122, "error": null, "frequency_penalty": 0, "gatewayMetadata": { "keySource": "Unified" }, "id": "resp_00272dd8da5b37c90169ebb1aaeb288194a6e5ddeb7bb03dc8", "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_00272dd8da5b37c90169ebb1faf90c81948fd9a67a37b4c209", "summary": [], "type": "reasoning" }, { "content": [ { "annotations": [], "logprobs": [], "text": "The **three laws of thermodynamics** usually mean:\n\n1. **First Law — Conservation of Energy** \n Energy cannot be created or destroyed, only transferred or transformed. \n - In thermodynamics: the change in a system’s internal energy equals heat added to the system minus work done by the system.\n\n2. **Second Law — Entropy Increases** \n In any natural process, the total entropy of an isolated system tends to increase. \n - This means energy spontaneously spreads out, and no heat engine can be 100% efficient.\n - Heat naturally flows from hot objects to cold ones, not the reverse without input of work.\n\n3. **Third Law — Entropy at Absolute Zero** \n As temperature approaches **absolute zero** (0 K), the entropy of a perfect crystal approaches zero. \n - A consequence is that absolute zero cannot be reached in a finite number of steps.\n\nSmall note: thermodynamics also has a **Zeroth Law**, which is often listed before these:\n- If system A is in thermal equilibrium with B, and B is in thermal equilibrium with C, then A is in thermal equilibrium with C. \n- This is the basis for the concept of **temperature**.\n\nIf you want, I can also give a **one-line intuitive version** of each law.", "type": "output_text" } ], "id": "msg_00272dd8da5b37c90169ebb1fafad0819488ef71fbebf8527a", "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": 15, "input_tokens_details": { "cached_tokens": 0 }, "output_tokens": 342, "output_tokens_details": { "reasoning_tokens": 67 }, "total_tokens": 357 }, "user": null} ``` ## Examples **With Instructions** — Using instructions to set context * [ TypeScript ](#tab-panel-1312) * [ cURL ](#tab-panel-1313) TypeScript ``` const response = await env.AI.run( 'openai/gpt-5.4-pro', { input: 'How do I read a JSON file in Python?', instructions: 'You are a helpful coding assistant specializing in Python.', },)console.log(response) ``` Terminal window ``` 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": "How do I read a JSON file in Python?", "instructions": "You are a helpful coding assistant specializing in Python."}' ``` * [ Output ](#tab-panel-1322) * [ Raw response ](#tab-panel-1323) Use Python’s built-in `json` module. ### Read a JSON file into a Python object ```python import json with open("data.json", "r", encoding="utf-8") as f: data = json.load(f) print(data) ``` ### What you get back `json.load()` converts JSON into normal Python types: - JSON object → `dict` - JSON array → `list` - JSON string → `str` - JSON number → `int` / `float` - JSON true/false → `True` / `False` - JSON null → `None` ### Example If `data.json` contains: ```json { "name": "Alice", "age": 30, "skills": ["Python", "SQL"] } ``` Then: ```python import json with open("data.json", "r", encoding="utf-8") as f: data = json.load(f) print(data["name"]) # Alice print(data["skills"]) # ['Python', 'SQL'] ``` ### Handle errors safely ```python import json try: with open("data.json", "r", encoding="utf-8") as f: data = json.load(f) except FileNotFoundError: print("File not found.") except json.JSONDecodeError: print("Invalid JSON.") ``` ### If you already have JSON as a string Use `json.loads()` instead: ```python import json text = '{"name": "Alice", "age": 30}' data = json.loads(text) print(data) ``` If you want, I can also show how to **write JSON back to a file**. ``` { "background": false, "billing": { "payer": "developer" }, "completed_at": 1777054145, "created_at": 1777054123, "error": null, "frequency_penalty": 0, "gatewayMetadata": { "keySource": "Unified" }, "id": "resp_00e5a81e42bf0bda0169ebb1ab449c8190a0d57802b4aebebd", "incomplete_details": null, "instructions": "You are a helpful coding assistant specializing in Python.", "max_output_tokens": null, "max_tool_calls": null, "metadata": {}, "model": "gpt-5.4-pro-2026-03-05", "moderation": null, "object": "response", "output": [ { "id": "rs_00e5a81e42bf0bda0169ebb1c0e57881909eaf01efa0557a43", "summary": [], "type": "reasoning" }, { "content": [ { "annotations": [], "logprobs": [], "text": "Use Python’s built-in `json` module.\n\n### Read a JSON file into a Python object\n```python\nimport json\n\nwith open(\"data.json\", \"r\", encoding=\"utf-8\") as f:\n data = json.load(f)\n\nprint(data)\n```\n\n### What you get back\n`json.load()` converts JSON into normal Python types:\n\n- JSON object → `dict`\n- JSON array → `list`\n- JSON string → `str`\n- JSON number → `int` / `float`\n- JSON true/false → `True` / `False`\n- JSON null → `None`\n\n### Example\nIf `data.json` contains:\n```json\n{\n \"name\": \"Alice\",\n \"age\": 30,\n \"skills\": [\"Python\", \"SQL\"]\n}\n```\n\nThen:\n```python\nimport json\n\nwith open(\"data.json\", \"r\", encoding=\"utf-8\") as f:\n data = json.load(f)\n\nprint(data[\"name\"]) # Alice\nprint(data[\"skills\"]) # ['Python', 'SQL']\n```\n\n### Handle errors safely\n```python\nimport json\n\ntry:\n with open(\"data.json\", \"r\", encoding=\"utf-8\") as f:\n data = json.load(f)\nexcept FileNotFoundError:\n print(\"File not found.\")\nexcept json.JSONDecodeError:\n print(\"Invalid JSON.\")\n```\n\n### If you already have JSON as a string\nUse `json.loads()` instead:\n```python\nimport json\n\ntext = '{\"name\": \"Alice\", \"age\": 30}'\ndata = json.loads(text)\nprint(data)\n```\n\nIf you want, I can also show how to **write JSON back to a file**.", "type": "output_text" } ], "id": "msg_00e5a81e42bf0bda0169ebb1c0e7608190b3928d22f252a21a", "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": 30, "input_tokens_details": { "cached_tokens": 0 }, "output_tokens": 397, "output_tokens_details": { "reasoning_tokens": 35 }, "total_tokens": 427 }, "user": null} ``` **Multi-turn Conversation** — Continuing a conversation with message array * [ TypeScript ](#tab-panel-1318) * [ cURL ](#tab-panel-1319) TypeScript ``` const response = await env.AI.run( 'openai/gpt-5.4-pro', { input: [ { content: 'I need help planning a road trip from San Francisco to Los Angeles.', role: 'user', }, { content: "I'd be happy to help! The drive is about 380 miles and takes roughly 5-6 hours. Would you like suggestions for scenic routes or interesting stops along the way?", role: 'assistant', }, { content: 'Yes, name three good stops in one short sentence each.', role: 'user' }, ], max_output_tokens: 16000, },)console.log(response) ``` Terminal window ``` 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": [ { "content": "I need help planning a road trip from San Francisco to Los Angeles.", "role": "user" }, { "content": "I'\''d be happy to help! The drive is about 380 miles and takes roughly 5-6 hours. Would you like suggestions for scenic routes or interesting stops along the way?", "role": "assistant" }, { "content": "Yes, name three good stops in one short sentence each.", "role": "user" } ], "max_output_tokens": 16000}' ``` * [ Output ](#tab-panel-1324) * [ Raw response ](#tab-panel-1325) - 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} ``` **Temperature Control** — Using temperature for creative responses * [ TypeScript ](#tab-panel-1314) * [ cURL ](#tab-panel-1315) TypeScript ``` const response = await env.AI.run( 'openai/gpt-5.4-pro', { input: 'Write a haiku about artificial intelligence', temperature: 1 },)console.log(response) ``` Terminal window ``` 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}' ``` * [ Output ](#tab-panel-1326) * [ Raw response ](#tab-panel-1327) 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} ``` **With Reasoning** — Using reasoning effort for complex problems * [ TypeScript ](#tab-panel-1316) * [ cURL ](#tab-panel-1317) TypeScript ``` 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) ``` Terminal window ``` 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" }}' ``` * [ Output ](#tab-panel-1328) * [ Raw response ](#tab-panel-1329) 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} ``` ## Parameters * [ Input ](#tab-panel-1330) * [ Output ](#tab-panel-1331) ▶input `one of`required instructions `string` temperature `number`minimum: 0maximum: 2 max\_output\_tokens `number`exclusiveMinimum: 0 top\_p `number`minimum: 0maximum: 1 stream `boolean` ▶tools\[\] `array` tool\_choice `` ▶text{} `object` ▶reasoning{} `object` id `string` object `string`const: response created\_at `number` model `string` ▶output\[\] `array` output\_text `string` status `string`enum: in\_progress, completed, failed, incomplete ▶usage{} `object` ## API Schemas (Raw) Input [ ](https://developers.cloudflare.com/ai/models/openai/gpt-5.4-pro/schema-input.json "Open") [ ](https://developers.cloudflare.com/ai/models/openai/gpt-5.4-pro/schema-input.json "Download") Output [ ](https://developers.cloudflare.com/ai/models/openai/gpt-5.4-pro/schema-output.json "Open") [ ](https://developers.cloudflare.com/ai/models/openai/gpt-5.4-pro/schema-output.json "Download") ```json {"@context":"https://schema.org","@type":"TechArticle","@id":"https://developers.cloudflare.com/ai/models/openai/gpt-5.4-pro/#page","headline":"GPT-5.4 pro (OpenAI) · Cloudflare AI docs · Cloudflare AI docs","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/dev-products-preview.png","publisher":{"@type":"Organization","name":"Cloudflare","url":"https://www.cloudflare.com/"},"isPartOf":{"@type":"WebSite","@id":"https://developers.cloudflare.com/#website","name":"Cloudflare Docs","url":"https://developers.cloudflare.com/"}} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"item":{"@id":"/directory/","name":"Directory"}},{"@type":"ListItem","position":2,"item":{"@id":"/ai/","name":"AI"}},{"@type":"ListItem","position":3,"item":{"@id":"/ai/models/","name":"Models"}}]} ```