GPT-3.5 Turbo
GPT-3.5 Turbo first brought ChatGPT-class conversational AI to the API at scale, delivering the same underlying capability at a price point that opened the door to production applications.
View API reference- Input and output price
- Input $0.50, Output $1.50, Per 1M tokens
- 24h uptime
- Loading AI Gateway uptime
import { streamText } from 'ai'
const result = streamText({ model: 'openai/gpt-3.5-turbo', prompt: 'Why is the sky blue?'})Copy link to headingPlayground
Try out GPT-3.5 Turbo by OpenAI. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days.
GPT-3.5 Turbo
GPT-3.5 Turbo
Copy link to headingProviders
Route requests across multiple providers. Copy a provider slug to set your preference. Visit the docs for more info. Using a provider means you agree to their terms, listed under Legal.
Copy link to headingUptime24 hours
Direct request success rate on AI Gateway and per-provider. Visit the docs for more info.
Copy link to headingThroughput24 hours
P50 throughput on live AI Gateway traffic, in tokens per second (TPS). Visit the docs for more info.
Copy link to headingLatency24 hours
P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds. View the docs for more info.
Getting started
Call GPT-3.5 Turbo through AI Gateway with the AI SDK generateText and streamText functions, or through the OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages APIs by changing the base URL. AI Gateway authenticates the request and routes it to an available provider.
Install the AI SDK (pnpm add ai dotenv), create an API key from the API Keys page, and set it as AI_GATEWAY_API_KEY in your environment. Full setup is covered in the text generation quickstart.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'openai/gpt-3.5-turbo', prompt: 'Why is the sky blue?', });
console.log(result.text);}
main().catch(console.error);Top-level parameters
The same GPT-3.5 Turbo request in each API format AI Gateway supports.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'openai/gpt-3.5-turbo', system: 'You are a concise technical assistant.', prompt: 'Summarize the tradeoffs between static generation and SSR.', maxOutputTokens: 1024, temperature: 0.5, });
console.log(result.text);}
main().catch(console.error);Standard parameters like prompt, messages, temperature, and tools work as documented in the AI SDK docs. These are the parameters with model-specific behavior.
| Parameter | Type | Required | Description |
|---|---|---|---|
model | string | Yes | Model ID in the form creator/model, e.g. openai/gpt-3.5-turbo. AI Gateway routes the request to an available provider. |
maxOutputTokens | number | No | Hard cap on generated tokens. GPT-3.5 Turbo supports up to 4,096 output tokens. |
providerOptions | Record<string, JSONValue> | No | AI Gateway routing options under gateway, plus any provider-native options under the provider’s own namespace — see the table below. |
Input limits
| Input | Formats | Sources | Max count | Max size | Limits |
|---|---|---|---|---|---|
| Text | — | — | — | — | Prompt and response share the 16K-token context window |
Provider options
Set AI Gateway routing options under providerOptions.gateway. For provider-specific options, pass them under the provider’s namespace as documented by the AI SDK.
Learn more in the AI SDK openai provider docs.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'openai/gpt-3.5-turbo', prompt: 'Why is the sky blue?', providerOptions: { gateway: { only: ['openai'], }, }, });
console.log(result.text);}
main().catch(console.error);These AI Gateway routing options apply to every model. Provider-specific options pass through under the provider’s own namespace (for example providerOptions.anthropic) exactly as documented by the AI SDK.
| Parameter | Type | Required | Description |
|---|---|---|---|
providerOptions.gateway.only | string[] | No | Restrict routing to these provider slugs. Requests fail over only within the listed providers. |
providerOptions.gateway.order | string[] | No | Preferred provider order. Listed providers are tried first; unlisted providers remain available as fallbacks. |
providerOptions.gateway.sort | 'cost' | 'ttft' | 'tps' | No | Rank candidate providers by price, time to first token, or tokens per second instead of the default routing order. |
providerOptions.gateway.zeroDataRetention | boolean | No | Route only to providers with a zero-data-retention policy for this model. |
Routing across providers
AI Gateway serves the same model through multiple providers and fails over automatically. order expresses a preference while keeping every provider eligible; only is a hard allowlist — if none of the listed providers are available the request fails instead of falling back.
Options under a provider's own namespace (for example providerOptions.anthropic) are forwarded to that provider with the request. Providers ignore option namespaces that don't apply to them, so it is safe to set provider options alongside gateway routing options.
Tool calling
Expose tools the model can call. Define each tool’s inputs with a Zod schema.
import { generateText, tool } from 'ai';import { z } from 'zod';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'openai/gpt-3.5-turbo', prompt: 'What is the weather in San Francisco?', tools: { getWeather: tool({ description: 'Get the current weather for a location', inputSchema: z.object({ location: z.string() }), execute: async ({ location }) => ({ location, temperatureC: 18 }), }), }, });
console.log(result.text);}
main().catch(console.error);Copy link to headingMore models by OpenAI
| Model |
|---|
| 1.1M | 2.9 s | 56 tps | $10/M+2 more | $50/M+2 more | Read$1/M Write$12.50/M | $10/K | +4 |  | 09/04/2026 | |||||
| 1.1M | 2.4 s | 156 tps | $0.20/M+2 more | $1.20/M+2 more | Read$0.02/M Write$0.25/M | $10/K | +4 |  | 07/09/2026 | |||||
| 1.1M | 2.6 s | 69 tps | $2/M+2 more | $10/M+2 more | Read$0.20/M Write$2.50/M | $10/K | +4 | | 07/09/2026 | |||||
| 1.1M | 2.6 s | 94 tps | $2/M+2 more | $12/M+2 more | Read$0.20/M Write$2.50/M | $10/K | +4 | | 07/09/2026 | |||||
| 1.1M | 3.5 s | 88 tps | $2.50/M+2 more | $15/M+2 more | Read$0.25/M | $10/K | +4 | | 03/05/2026 | |||||
| 400K | 4.4 s | 208 tps | $0.05/M | $0.40/M | Read$0.005/M | $14/K | +3 | | 08/07/2025 |
Copy link to headingAbout GPT-3.5 Turbo
GPT-3.5 Turbo launched on March 1, 2023 alongside the Whisper API as OpenAI opened its ChatGPT capability to developers through a dedicated API endpoint. At introduction it cost substantially less than the existing GPT-3.5 models, making it the first model to put conversational AI within budget for production-scale products.
The model uses a conversational message format where developers supply a list of messages with roles (system, user, assistant) rather than a single prompt string. This chat-native interface made it straightforward to build multi-turn experiences, chatbots, and instruction-following assistants without extra prompt engineering to simulate turns.
Over subsequent months OpenAI expanded the model: a 16K context variant arrived to handle roughly 20 pages of text in one request, and the standard model received a price reduction together with improved function-calling capabilities and better steerability. It remains widely deployed for workloads where conversational throughput and cost efficiency outweigh the need for frontier reasoning depth.
Copy link to headingWhat To Consider When Choosing a Provider
- Configuration: If you run high message volumes and per-token cost is your dominant concern, GPT-3.5 Turbo remains one of the most economical options for straightforward conversational workloads.
- Zero Data Retention: Zero Data Retention is offered on a per-provider and model basis. See the documentation for details.
- Authentication: AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.
Copy link to headingWhen to Use GPT-3.5 Turbo
Best for
- Customer support bots: FAQ systems where fast, on-topic replies matter more than complex reasoning
- Summarization pipelines: Processing large numbers of documents at low cost
- Draft generation: Emails, support tickets, or templated content at volume
- Multi-turn chat: Consumer or internal tools where latency and price sensitivity are high
- Lightweight classification: Intent detection tasks embedded in larger automation pipelines
Consider alternatives when
- Advanced reasoning needed: Multi-step logical reasoning, math, or code generation where GPT-4-class accuracy is necessary
- Very long prompts: Your prompt regularly exceeds the context window and you need the full 1M-token range of GPT-4.1
- Multimodal input: You need native vision or audio input processing
- Strict instruction adherence: Complex, structured tasks where errors are costly
Copy link to headingConclusion
GPT-3.5 Turbo combined ChatGPT-class quality with a pricing tier that made scaling practical. For chat, summarization, and instruction-following workloads where cost per call is the primary constraint, it remains a solid option through AI Gateway.
Copy link to headingFrequently Asked Questions
What API format does GPT-3.5 Turbo use?
It uses the Chat Completions API format. You send an array of messages with roles (
system,user,assistant) rather than a raw completion prompt string.How does GPT-3.5 Turbo differ from GPT-3.5 Turbo Instruct?
GPT-3.5 Turbo is built for the Chat Completions endpoint and conversational multi-turn use. GPT-3.5 Turbo Instruct targets the legacy Completions endpoint and is optimized for single-turn instruction tasks using a prompt-response format.
What context window does GPT-3.5 Turbo support?
The current model supports a context window of 16.4K tokens, suitable for multi-turn conversations and moderate-length document tasks.
Is GPT-3.5 Turbo suitable for function calling?
Yes. OpenAI added function-calling support, enabling developers to define external functions the model can invoke, making it viable for agentic and tool-use workflows within its capability tier.
How does AI Gateway handle authentication for GPT-3.5 Turbo?
AI Gateway accepts a single API key or OIDC token for all requests. You don't embed OpenAI credentials in your application; AI Gateway routes and authenticates on your behalf.
Can I use GPT-3.5 Turbo for batch summarization pipelines?
Yes. Its combination of low per-token cost, fast response times, and context window of 16.4K tokens makes it well-suited for pipelines that process many documents in parallel.
What are typical latency characteristics?
This page shows live throughput and time-to-first-token metrics measured across real AI Gateway traffic.