GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks.
Training data up to Sep 2021.
Modalities
Input Price
$1per 1M
Output Price
$2per 1M
Context
4K
Weekly Tokens
14.2M
Released
Jan 25, 2024
Sample code and API for GPT-3.5 Turbo (older v0613)
OpenRouter normalizes requests and responses across providers for you.
1
Get your API key
Create an API key from your OpenRouter dashboard and set it as an environment variable:
2
Make your first request
Use openai/gpt-3.5-turbo-0613 with the OpenRouter API:
OpenRouter provides an OpenAI-compatible completion API to 400+ models & providers that you can call directly, or using the OpenAI SDK. Additionally, some third-party SDKs are available.
In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.
Using third-party SDKs
For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.
3
Enable streaming
Add "stream": true to your request body to receive responses as server-sent events:
Endpoint
POSThttps://openrouter.ai/api/v1/chat/completions
AuthorizationBearer $OPENROUTER_API_KEY
Content-Typeapplication/json
HTTP-Refereroptional — your site URL, for rankings
X-Titleoptional — your site name, for rankings
Modelopenai/gpt-3.5-turbo-0613
Parameters
Name
Type
Default
Description
max_completion_tokens
integer
—
This sets the upper limit for the number of tokens the model can generate in response.
temperature
float
1
This setting influences the variety in the model's responses.
top_p
float
1
This setting limits the model's choices to a percentage of likely tokens: only the top tokens whose probabilities add up to P.
stop
array
—
Stop generation immediately if the model encounter any token specified in the stop array.
frequency_penalty
float
0
This setting aims to control the repetition of tokens based on how often they appear in the input.
presence_penalty
float
0
Adjusts how often the model repeats specific tokens already used in the input.
seed
integer
—
If specified, the inferencing will sample deterministically, such that repeated requests with the same seed and parameters should return the same result.
logit_bias
map
—
Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100.
logprobs
boolean
—
Whether to return log probabilities of the output tokens or not.
top_logprobs
integer
—
An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability.
response_format
map
—
Forces the model to produce specific output format.
tools
array
—
Tool calling parameter, following OpenAI's tool calling request shape.
tool_choice
string or object
—
Controls which (if any) tool is called by the model.