GPT-5.2 Chat API: Endpoint & 30% Discount
Deprecated 10 Aug 2026GPT-5.2 Chat is an OpenAI conversational language model designed for interactive dialogue and task assistance.
What is GPT-5.2 Chat?
GPT-5.2 Chat is a conversational AI model from OpenAI optimized for multi-turn dialogue and natural language understanding. It is mainly used for chat-based assistance, such as answering questions, drafting and editing text, and helping users reason through complex problems. It also supports integration into applications and workflows where reliable, instruction-following dialogue is required. GPT-5.2 Chat belongs to OpenAI’s GPT family of large language models, following earlier generations such as GPT-3 and GPT-4.
Can you self-host GPT-5.2 Chat?
No. We found no public weights for GPT-5.2 Chat on Hugging Face, so there is nothing to download, quantize or serve on your own GPUs: no VRAM budget, no vLLM or GGUF build to plan for. The only way to run it is over an API.
Not on LLM.API yet
We do not route this model through our API at the moment. Browse the models you can call today — most workloads have a close match already live.
Providers
Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Exacto (highest tool-calling accuracy).
List price by provider
InputOutputProvider list prices; the LLM.API discount applies on top.
| Provider | Input | Output | Cache read /M | Latency | Throughput | Uptime |
|---|---|---|---|---|---|---|
| in $1.75; out $14 per 1M tokens | 128K tokens | vision, tools, streaming, reasoning, web search, JSON, structured |
Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 27 Sept 2026.
Try this model
Test GPT-5.2 Chat right here — free to start.
Suggestions for your first prompt
Not available on LLM API yet
We do not route this model through our API at the moment, so there is no endpoint or code snippet for it yet. Browse the models you can call today — most workloads have a close match already live.
Browse available modelsUptime
Last 30 days
26/30 days operational | 96.70% uptime
GPT-5.2 Chat in production
What the model is good at.
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Conversational Chat
Engages in multi-turn conversations, maintaining context, following instructions, and adapting tone for assistance, brainstorming, and problem-solving.
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Code Reasoning
Understands, writes, and explains code across multiple languages, assisting with debugging, refactoring, and algorithmic reasoning tasks.
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Image Understanding
Interprets images to identify objects, text, layouts, and visual relationships, supporting analysis, explanation, and content extraction.
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Text Translation
Translates between many languages, preserving meaning and style, and can clarify ambiguities or cultural nuances when needed.
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Visual Text OCR
Extracts readable text from images, including documents, screenshots, and signs, enabling search, editing, and downstream processing.
What you get when you call GPT-5.2 Chat through LLM.API.
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Dynamic AI Routing
Automatically route each request to the optimal model across providers based on latency, reliability, and capabilities, so you ship faster without hardcoding vendor logic.
One endpoint, any model -
Cost-Aware Orchestration
Balance quality and price with per-call cost controls, smart tiering, and spend visibility, letting you optimize inference budgets without rewriting application code.
Maximum performance per dollar -
Resilient Fallback Flows
Define automatic failover to backup models or providers on errors, timeouts, and rate limits, keeping your AI features online even when vendors aren’t.
Built-in reliability layer -
End-to-End Observability
Get centralized logs, traces, and metrics for every model call—latency, errors, and tokens—so you can debug issues and tune performance from a single dashboard.
See every token, everywhere -
Task-Level Abstractions
Describe tasks—chat, generation, tools, scoring—once and let LLM.API handle provider-specific quirks, so you focus on product logic instead of API plumbing.
Code to tasks, not vendors -
High-Throughput Batch Jobs
Run large-scale batch inference across models and providers with concurrency, retries, and progress tracking handled for you, ideal for backfills and async workloads.
Ship millions of calls safely
When to Use — When NOT to Use
Use it if...
- You need strong general-purpose chat, coding, and analysis with minimal integration overhead.
- You need advanced reasoning over complex instructions, including planning, refactoring, and debugging code.
- You need high-quality natural language generation for support bots, agents, or content drafting.
- You need tight integration with other OpenAI models, tools, or function-calling ecosystems.
- Your use case involves multi-step workflows where the assistant must maintain long, coherent context.
- You need good performance on ambiguous user queries that require clarification and safe handling.
- Your use case involves mixing natural language, structured data, and light mathematical reasoning.
Avoid if...
- You need strict on-premise deployment with no external API calls or cloud dependency.
- Your workload requires ultra-low latency, sub-50ms responses for tight real-time interactivity.
- You need deterministic, auditable outputs where non-probabilistic rule-based systems are mandatory.
- Your workload requires heavy, high-frequency numerical computation better suited to traditional GPU code.
- You need guaranteed compliance with highly specialized domain regulations beyond configurable policies.
- Your workload requires fully offline operation, disconnected from the internet or external services.
- You need a tiny, device-embedded model optimized for inference on low-power hardware.
COMMUNITY
What developers say about GPT-5.2 Chat
Summarised from public developer discussions and write-ups. Opinions are the sources’, not LLM.API’s.
- Developers on Reddit report GPT-5.2-chat-latest is highly effective at following project Markdown workflows and fixing both frontend and backend bugs in a single pass.
- Developers on the OpenAI community site observe that the chat-latest variant operates in a permanent reasoning mode, using default medium effort and producing responses frequently containing emojis.
- Some developers note that while the model is powerful, it may stop early, require more extensive prompt engineering, and occasionally lose context continuity during long tasks.
SOURCES
Frequently Asked Questions
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What is GPT-5.2 Chat?
GPT-5.2 Chat is a state-of-the-art OpenAI conversational language model accessible through the LLM.API unified gateway for general-purpose and agentic applications.
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What is GPT-5.2 Chat best suited for?
GPT-5.2 Chat excels at complex multi-step reasoning, tool-using agents, high-quality coding assistance, and production chatbots requiring reliable, steerable behavior.
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What modalities does GPT-5.2 Chat support via LLM.API?
GPT-5.2 Chat supports text input and output via LLM.API; additional modalities depend on LLM.API’s configured OpenAI feature support.
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How is GPT-5.2 Chat priced on LLM.API?
GPT-5.2 Chat pricing is defined by LLM.API’s OpenAI-backed tariff; refer to your LLM.API dashboard or pricing docs for current per-token rates.
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What context window does GPT-5.2 Chat support?
GPT-5.2 Chat supports a large context window; check the LLM.API model metadata for the exact maximum tokens for your deployment.
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How fast is GPT-5.2 Chat in terms of latency?
Typical end-to-end latency depends on prompt size and LLM.API infrastructure, but GPT-5.2 Chat is optimized for responsive interactive use.
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How do I call GPT-5.2 Chat through the LLM.API?
Specify the model identifier "GPT-5.2 Chat" in your LLM.API completion or chat endpoint request, plus your prompt and any desired parameters.
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How does GPT-5.2 Chat compare to earlier GPT-4.x models?
GPT-5.2 Chat generally provides stronger reasoning, better adherence to instructions, and improved coding capabilities compared with GPT-4.x-class models.
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What limitations does GPT-5.2 Chat have?
GPT-5.2 Chat can still hallucinate, reflect outdated knowledge, and must not be solely relied on for high-stakes domains without external verification.
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Can GPT-5.2 Chat use tools or functions through LLM.API?
Yes, if LLM.API exposes a tool-calling interface, GPT-5.2 Chat can be configured to call tools or functions based on your schema.
COMPARE
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$1.4 in / $4.4 out per 1M tokens, 202,800 context — the closest current alternative to GPT-5.2 Chat.
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GPT-5.5
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