Extract these synthetic records into JSON with fields id, owner, deadline and evidence: [R1] Issue 41: Ana owns the export fix; no deadline agreed. [R2] Issue 42: review due October 15; owner not assigned; year not stated. Use null for missing values and preserve partial dates as given. Quote the source in evidence. Do not invent a year or owner. Check each field against its record; this is a text-formatting task, not a database operation.
GPT 5.4 API: Pricing, Playground and Examples
Review GPT 5.4 API token pricing and Chat Completions or Responses examples for document analysis, structured extraction and code review.
GPT 5.4 API pricing and billing
Pricing and availability are currently unavailable. Check account pricing and model availability before submitting a paid request.
GPT 5.4 online chat tool
Model settings
What does memory do?
It includes completed, reusable turns from this conversation in your next request, so you can ask follow-up questions without repeating the context.
What happens when it is off?Only your new message and any system prompt are sent. Existing messages stay visible; turning memory back on includes eligible earlier turns again.
Is this long-term memory?No. This is conversation context, not memory across separate conversations. Failed, stopped, truncated, or non-reusable replies are excluded. More history can use more input tokens and increase cost.
Advanced parameters
0 or more characters(0/No fixed limit)
No fixed character limit; the full request is subject to request-size and model-context limits. This is not a token count. Conversation
How can I help you today?
No response data yet Ready
GPT 5.4 prompt examples
These are evaluation prompts for GPT 5.4, not recorded model outputs. They analyze only supplied text; they do not execute code, inspect production systems or prove long-context performance. Check quoted evidence and acceptance criteria, then review response metadata and usage before production use.
Use only this document sample: [P1] The export fix passed staging checks. [P2] A Friday release was proposed, not approved. [P3] Mei will review error messages on Tuesday. [P4] No owner is assigned to documentation. Return a table of claim, exact supporting quote, paragraph ID and uncertainty. Is production release approved? Who owns documentation? Mark missing facts unknown. Every quote must match the supplied sample; do not infer production success from staging. This small sample does not test maximum context length.
Review this fictional payment-webhook policy: every failed POST is retried three times, no idempotency key is stored, and the balance is debited before the response is sent. Identify duplicate-charge risks, propose minimal changes and three acceptance tests. Use only these facts; do not assume access to code, tools or production systems.
What is GPT 5.4?
GPT 5.4 model focus and core capabilities
GPT 5.4 is an OpenAI model for coding and professional work, combining text reasoning with image understanding and a native 1,050,000-token context window. It is a candidate for workflows that move between technical analysis, document synthesis, and software development rather than a model restricted to writing short summaries.
GPT 5.4 online tools and API on API Hop
API Hop provides an online text Playground, unified Chat Completions, and OpenAI-compatible Responses access for gpt-5.4. Test supplied text here before integrating your application. The text tool does not upload files, browse websites, or execute code; multimodal requests and tools require the appropriate documented interface and supported configuration.
GPT 5.4 capabilities and domain strengths
GPT 5.4 can help connect project requirements, technical material, and a proposed deliverable. Make the task checkable: define what must remain unchanged, what evidence is available, and what a useful answer should contain.
Coding assistance across requirements and implementation
Supply related modules, an observed failure, and acceptance tests to ask for a diagnosis and a focused change proposal. GPT 5.4 can assist with code review, interface design, and explaining how a change affects callers, rather than only completing a function in isolation.
Ask it to separate verified observations from hypotheses and include tests for the suspected failure. Your development environment must compile and run any proposed patch; this Playground cannot inspect a repository or establish that generated code works.
Long context for traceable document synthesis
A native 1,050,000-token context window creates room for extensive source material. For a project brief, provide numbered passages and ask for confirmed decisions, unresolved approvals, owners, and risks with references to the supplied text.
A large window is not a guarantee of complete recall. Select relevant material, preserve document versions, and audit omissions as well as invented additions. Actual request size and allowance depend on API Hop and the upstream channel, not only the model specification.
Image understanding with a distinct API input path
GPT 5.4 supports image input at the model level. Visual analysis can support reviewing a chart, interpreting an interface layout, or relating a diagram to accompanying technical notes when the image is sent through a supported multimodal interface.
This text Playground has no image or PDF upload control. API Hop Responses documents public image URLs in input_image and PDF content in input_file; follow those formats instead of assuming a pasted link is analyzed. Audio and video are not native input modalities for this model.
Adjustable reasoning and structured deliverables
GPT 5.4 supports configurable reasoning effort and structured outputs at the model level. A decision brief can request a recommendation, the constraints supporting it, and conditions that would reverse it; an extraction task can define fields, types, and missing-value behavior.
Parameter support must be checked on the chosen interface. A natural-language JSON request is not schema enforcement, and schema-valid data can still be incorrect. Validate source alignment and business rules, especially before using financial, legal, or other consequential material.
How to evaluate GPT 5.4 for your workload
Published model evaluations and your application results answer different questions. Treat coding, document, and tool benchmarks as candidate-selection signals, not a promise of API Hop response time, availability, or success on your own workload.
| Task input | Checks | Pass criteria | Metrics to record |
|---|---|---|---|
| A brief with conflicting versions, tentative dates, and missing owners | Check citations, field values, and unresolved commitments | Every required field is source-backed; missing values stay unknown | Correct and invented fields, omissions, rework, duration, token usage |
Evaluate coding against executable acceptance tests
For software work, measure whether a patch resolves the reported issue, preserves existing behavior, and passes relevant tests. Include cases requiring more than one file and track invented APIs, missed dependencies, and unnecessary changes.
A tool-enabled benchmark includes a harness that supplies files and execution feedback. A single text reply does not have that environment. Compare models using the same repository context and validation process rather than converting a benchmark score into a predicted repair rate.
Evaluate document accuracy beyond fluent prose
Use briefs with tentative dates, conflicting versions, missing owners, and numerical exceptions. Check that GPT 5.4 retains uncertainty, cites supplied passages correctly, and distinguishes a proposed action from an existing commitment.
For structured extraction, count correct fields and unsupported inferences separately from JSON parsing success. For visual work, evaluate the actual image input path; a text-only description cannot validate image perception or PDF understanding.
Measure quality, latency, and usage together
Keep prompts, protocol, history, and output requirements comparable. Record source accuracy, rework, time to first visible text, total duration, and actual usage. Compare reasoning configurations only when the selected channel supports them.
Long inputs and repeated history can increase cost, while reasoning may delay visible text and consume output allowance. Choose settings from a small representative sample; no local production latency or benchmark score is claimed here.
GPT 5.4 compared with GPT and Claude models
Use GPT 5.4 as one candidate for a defined workload, then compare related catalog models with identical acceptance criteria. The table describes evaluation tasks rather than an unverified performance ranking.
| Dimension | GPT 5.4 | Related candidates | Validation method |
|---|---|---|---|
| Code changes | Review requirements and propose patches | GPT 5.5, Claude Sonnet 5.5 | Run tests and inspect change scope |
| Document synthesis | Create source-aligned briefs | GPT 5.5, Kimi K3 | Check facts, omissions, and uncertainty |
| Structured extraction | Define fields and missing values | GPT 5.6 Terra | Validate schema and every source field |
| API integration | Chat Completions and Responses | Protocol varies by candidate | Check catalog, request body, and output parsing |
When to prioritize testing GPT 5.4
Start with GPT 5.4 when one workflow combines technical reasoning, source-backed writing, and coding assistance, or when you need to evaluate both Chat Completions and Responses integration. A useful sample is a project brief that also asks for a change plan and associated regression tests.
Do not infer that another version is always better, or that a familiar SDK makes every feature portable. Compare the answer quality and current account price under the protocol your application will actually use.
Choose models by task on API Hop
Confirm access for your API key through GET /v1/models, then compare candidates using the same inputs and acceptance criteria.
Compare GPT 5.5 for the same difficult brief, Claude Sonnet 5.5 for code review, Kimi K3 for source-heavy synthesis, and GPT 5.6 Terra for structured extraction. These are evaluation candidates, not claims that one necessarily wins its assigned task.
The common text interface helps reuse authentication and message structure. Responses and Messages use different contracts, and model-specific parameters can differ even within a family. Preserve a common rubric while checking each candidate page and documentation.
Why use GPT 5.4 through API Hop?
Usage-based billing and model cost optimization
Charges follow current API Hop rates and actual usage. Top up on demand.
Unified AI models and data APIs, with multi-model access in one place
One API key connects multiple AI models and data services, reducing integration costs and letting you switch with one click. Business applications need both AI and data.
Call logs and application access controls, with clarity on every call
Every API call is recorded in your dashboard. Create separate API keys for different applications.
Evaluate outputs against your task
Use the documented model ID and supported parameters through API Hop. Evaluate outputs against your own acceptance criteria, then inspect usage records and response metadata before production use. A model name or example does not guarantee each result.
How to use GPT 5.4 on API Hop
After creating an API key in the console, follow the documentation to get started with GPT 5.4.
Prepare your account and test online
Sign in, confirm your balance, and create an API key.
Try it in the Playground
Explore the model's capabilities in the Playground to find the best way to use it.
Integrate GPT 5.4 into your business
Follow our developer documentation to integrate GPT 5.4 into your business.
Future model upgrades
To switch to a newer model, first confirm that its exact ID is returned by the model catalog for your API key. If it supports the same endpoint and request fields, update the model ID, then test response formats, streaming, output limits and billing before sending production traffic. For asynchronous image or video tasks, also verify job submission, status polling and result retrieval.
GPT 5.4 API FAQ
Can the GPT 5.4 Playground accept images, PDFs, or video?
This Playground accepts text and has no file upload control. GPT 5.4 supports image understanding, while API Hop Responses documents public image URLs through input_image and PDF Data URLs through input_file with filename. These are separate API inputs, not links pasted into chat. Audio and video are not native model inputs here.
Why might GPT 5.4 produce no final text or an incomplete answer?
A small explicit output budget can be consumed by reasoning or truncate final text. Check Chat finish_reason or Responses completion status and any incomplete details before treating the result as complete. Narrow the task or adjust the optional allowance. Do not assume that GPT 5.4 exposes raw internal reasoning or always returns reasoning_content.
Is conversation memory permanent, and why does usage grow?
Memory here is current conversation context, not persistent memory across sessions. Enabling it includes reusable completed turns, which can increase input usage. Disabling it leaves history visible but excludes it from new requests. Failed, stopped, truncated, or non-reusable replies are not appended as normal history. A Responses response ID alone does not guarantee stateful continuation on every channel.
How should I troubleshoot 401, 402, 403, or 429 errors?
For 401, check the key and Bearer authentication; for 402, check balance; for 403, check gpt-5.4 permissions; for 429, check request rate or allowance. Confirm availability through the catalog for your key. The numeric platform code is separate from the HTTP status; inspect full error details for upstream failures and in-stream SSE errors rather than treating every failure as an invalid key.
Can I call GPT 5.4 using OpenAI Responses or Claude Messages?
API Hop lists gpt-5.4 for Chat Completions and OpenAI-compatible Responses, not Claude Messages. Responses uses input and output items; Chat uses messages and choices. Select the matching endpoint and parser rather than only changing the model name. Ordinary Responses support does not imply Compact or stateful continuation is available on your channel.
Can one request return multiple alternatives or guarantee valid JSON?
Ask for several alternatives within one reply instead of assuming every protocol accepts n. Responses does not document n in its request contract. GPT 5.4 supports structured outputs at the model level, and Responses documents text.format; confirm your schema configuration on the selected channel. A JSON prompt alone is not enforcement, and schema-valid output still needs factual and business validation.
Can GPT 5.4 execute code, use tools, or perform business actions here?
The text Playground does not execute code, control a browser, change files, or make payments. Responses documents tool definitions, but actual tool availability depends on the channel. Your application must execute custom functions, return results, enforce permissions, and approve sensitive actions. A function call or generated plan is not proof of a completed operation.
Should I immediately retry a slow response, interrupted stream, or stopped request?
Check existing results, request records, and usage first. Long input and reasoning can affect response time. Stopping browser waiting or losing an SSE connection does not prove the upstream request was unprocessed. Avoid parallel duplicate retries; classify the error, check for outstanding results, and use bounded backoff when retrying is appropriate.
Related text APIs
GPT 5.4 API examples and supported parameters
GPT 5.4 API quickstart
gpt-5.4model is required; these examples use the current page model ID. Check model access for your API key with GET /v1/models.
Chat CompletionsPOST /v1/chat-completions
curl -X POST "https://api.apihop.ai/v1/chat-completions" \
-H "Authorization: Bearer <API_KEY>" \
-H "Content-Type: application/json" \
-d '{"model":"gpt-5.4","messages":[{"role":"user","content":"Hello, introduce yourself in one sentence."}],"stream":false}'ResponsesPOST /openai/responses
curl -X POST "https://api.apihop.ai/openai/responses" \
-H "Authorization: Bearer <API_KEY>" \
-H "Content-Type: application/json" \
-d '{"model":"gpt-5.4","input":"Hello, reply with one short sentence.","stream":false}'Family and protocol reference
OpenAI Multimodal Responses
Full API documentationOpenAI-compatible Responses API. This endpoint uses OpenAI-style `input`, supports text, public image URLs, PDF file input, tool calls, reasoning options, and streaming parameters.
POST
https://api.apihop.ai/openai/responses