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Sesame: CSM 1B

sesame/csm-1b

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CSM 1B is a conversational speech model from Sesame. It accepts text input and produces English speech output, with voice options spanning conversational and read-speech styles. At 1B parameters, it is suited for dialogue-oriented applications such as voice assistants and interactive agents.

Modalities

Price

$7/M characters

Context

4K

Released

Apr 23, 2026

Overview
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API

Sample code and API for CSM 1B

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 sesame/csm-1b with the OpenRouter API:

OpenRouter provides a text-to-speech API that converts text into natural-sounding audio. Send text and a voice selection, and receive raw audio bytes in your chosen format.

The response is a raw audio stream (not JSON). The generation ID is returned in the X-Generation-Id response header for tracking.

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

Endpoint

Synthesizes audio from the input text. Returns a raw audio bytestream in the requested format (e.g. mp3, pcm, wav).

POSThttps://openrouter.ai/api/v1/audio/speech
AuthorizationBearer $OPENROUTER_API_KEY
Content-Typeapplication/json
HTTP-Refereroptional — your site URL, for rankings
X-Titleoptional — your site name, for rankings
Modelsesame/csm-1b

Parameters

NameTypeDefaultDescription
max_tokensinteger—This sets the upper limit for the number of tokens the model can generate in response.
temperaturefloat1This setting influences the variety in the model's responses.
top_pfloat1This setting limits the model's choices to a percentage of likely tokens: only the top tokens whose probabilities add up to P.
stoparray—Stop generation immediately if the model encounter any token specified in the stop array.
frequency_penaltyfloat0This setting aims to control the repetition of tokens based on how often they appear in the input.
presence_penaltyfloat0Adjusts how often the model repeats specific tokens already used in the input.
repetition_penaltyfloat1Helps to reduce the repetition of tokens from the input.
top_kinteger0This limits the model's choice of tokens at each step, making it choose from a smaller set.
seedinteger—If specified, the inferencing will sample deterministically, such that repeated requests with the same seed and parameters should return the same result.
min_pfloat0Represents the minimum probability for a token to be considered, relative to the probability of the most likely token.
response_formatmap—Forces the model to produce specific output format.