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v1
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completions
import os
from cerebras.cloud.sdk import Cerebras

client = Cerebras(
    api_key=os.environ.get("CEREBRAS_API_KEY"),  # This is the default and can be omitted
)

completion = client.completions.create(
    prompt="It was a dark and stormy night",
    max_tokens=100,
    model="gpt-oss-120b",
    logprobs=5,
)

print(completion)

{
    "id": "chatcmpl-b1743f2d-8c20-4ad5-a77c-426521ae1b1c",
    "choices": [
        {
            "index": 0,
            "finish_reason": "length",
            "logprobs": {
                "text_offset": [30, 34, 40, 44, 47, 52],
                "token_logprobs": [
                    -3.3912997245788574,
                    -4.322617053985596,
                    -0.3532562553882599,
                    -1.7001153230667114,
                    -2.187103271484375,
                    -2.4667720794677734
                ],
                "tokens": [" and", " there", " was", " no", " moon", ","],
                "top_logprobs": [
                    {
                        ".": -1.1334871053695679,
                        ",": -1.3366121053695679,
                        " when": -2.3366122245788574,
                        " in": -2.9381747245788574,
                        "...": -3.3287997245788574,
                        " and": -3.3912997245788574
                    },
                    {
                        " I": -0.9554294943809509,
                        " the": -1.7679295539855957,
                        " a": -2.2366795539855957,
                        " all": -3.1898045539855957,
                        " we": -3.4241795539855957,
                        " there": -4.322617053985596
                    },
                    {
                        " was": -0.3532562553882599,
                        " were": -1.6813812255859375,
                        " I": -4.0251312255859375,
                        " wasn": -4.1345062255859375,
                        " had": -4.1970062255859375
                    },
                    {
                        " a": -0.3719903528690338,
                        " no": -1.7001153230667114,
                        " an": -3.614177942276001,
                        " this": -4.129802703857422,
                        " nothing": -4.184490203857422
                    },
                    {
                        " electricity": -1.3433531522750854,
                        " one": -1.6949156522750854,
                        " moon": -2.187103271484375,
                        " way": -3.038665771484375,
                        " sign": -3.054290771484375
                    },
                    {
                        ".": -0.8495846390724182,
                        " to": -2.1386470794677734,
                        " in": -2.2870845794677734,
                        ",": -2.4667720794677734,
                        ".\n": -3.2714595794677734
                    }
                ]
            },
            "text": " and there was no moon,",
            "tokens": null
        }
    ],
    "created": 1769297019,
    "model": "gpt-oss-120b",
    "object": "text_completion",
    "system_fingerprint": "fp_feb5e1faa8274e54bef0",
    "time_info": {
        "completion_time": 0.002412253,
        "prompt_time": 0.000347391,
        "queue_time": 0.000245702,
        "total_time": 0.004331350326538086,
        "created": 1769297019.2632425
    },
    "usage": {
        "completion_tokens": 6,
        "prompt_tokens": 8,
        "prompt_tokens_details": {
            "cached_tokens": 0
        },
        "total_tokens": 14
    }
}

Documentation Index

Fetch the complete documentation index at: https://inference-docs.cerebras.ai/llms.txt

Use this file to discover all available pages before exploring further.

Generate text continuations from a single prompt string. Best for simple text generation, autocomplete, and single-turn tasks.

​
Request

​
Headers

​
Content-Type
string
The media type of the request body.Supported values: application/json, application/vnd.msgpackDefault: application/jsonSee Payload Optimization for details.
​
Content-Encoding
string
The compression encoding applied to the request body.Supported values: gzipWhen set, the request body must be gzip-compressed. Can be combined with any supported Content-Type.See Payload Optimization for details.

​
Body

​
prompt
string | array
The prompt(s) to generate completions for, encoded as a string, array of strings, array of tokens, or array of token arrays. Default: ""
​
model
string
required
The model to use for completion. See Supported Models for a list of available models.
​
stream
boolean | null
If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message.Default: false
​
return_raw_tokens
boolean | null
Return raw tokens instead of text.Default: false
​
max_tokens
integer | null
The maximum number of tokens that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model’s context length.Default: null
​
min_tokens
integer | null
The minimum number of tokens to generate for a completion. If not specified or set to 0, the model will generate as many tokens as it deems necessary. Setting to -1 sets to max sequence length.Default: null
​
grammar_root
string | null
The grammar root used for structured output generation. Supported values: root, fcall, nofcall, insidevalue, value, object, array, string, number, funcarray, func, ws.Default: null
​
seed
integer | null
If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed.Default: null
​
stop
string | array | null
Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.Default: null
​
temperature
float | null
What sampling temperature to use, between 0 and 1.5. Higher values (e.g., 0.8) will make the output more random, while lower values (e.g., 0.2) will make it more focused and deterministic. We generally recommend altering this or top_p but not both.Minimum: 0, Maximum: 1.5Default: 1.0
​
top_p
float | null
An alternative to sampling with temperature, called nucleus sampling, where the model considers the tokens with top_p probability mass. For example, 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.Minimum: 0, Maximum: 1Default: 1.0
​
echo
boolean
Echo back the prompt in addition to the completion. Incompatible with return_raw_tokens=True.Default: false
​
user
string | null
A unique identifier representing your end-user, which can help Cerebras to monitor and detect abuse.Default: null
​
prompt_cache_key
string | null
An opaque identifier that groups related requests so they reuse the same prompt cache. Requests sharing the same prompt_cache_key are routed together, which increases cache hits and reduces time to first token.Set it to a stable identifier like a conversation ID, user ID, or session ID.Maximum length: 1024 charactersDefault: null
prompt_cache_key must be enabled on your account before you can use it. Contact us or reach out to your account representative to request access.
​
logprobs
integer | null
Return log probabilities of the output tokens.For example, if logprobs is 5, the API will return a list of the 5 most likely tokens. The API will always return the logprob of the sampled token, so there may be up to logprobs+1 elements in the response.Minimum: 0, Maximum: 20Default: null
Setting logprobs to 0 is different than null. When set to null, log probabilities are disabled entirely. When set to 0, log probabilities are enabled but it does not return top_logprobs.

​
Completion Response

​
choices
object[]
required
The list of completion choices the model generated for the input prompt.
​
created
integer | null
required
The Unix timestamp (in seconds) of when the completion was created.
​
id
string
A unique identifier for the completion.
​
model
string
The model used for completion.
​
object
string
required
The object type, which is always “text_completion”
​
system_fingerprint
string
This fingerprint represents the backend configuration that the model runs with.Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.
​
usage
object
Usage statistics for the completion request.
​
time_info
object
Performance timing information for the request.
import os
from cerebras.cloud.sdk import Cerebras

client = Cerebras(
    api_key=os.environ.get("CEREBRAS_API_KEY"),  # This is the default and can be omitted
)

completion = client.completions.create(
    prompt="It was a dark and stormy night",
    max_tokens=100,
    model="gpt-oss-120b",
    logprobs=5,
)

print(completion)

{
    "id": "chatcmpl-b1743f2d-8c20-4ad5-a77c-426521ae1b1c",
    "choices": [
        {
            "index": 0,
            "finish_reason": "length",
            "logprobs": {
                "text_offset": [30, 34, 40, 44, 47, 52],
                "token_logprobs": [
                    -3.3912997245788574,
                    -4.322617053985596,
                    -0.3532562553882599,
                    -1.7001153230667114,
                    -2.187103271484375,
                    -2.4667720794677734
                ],
                "tokens": [" and", " there", " was", " no", " moon", ","],
                "top_logprobs": [
                    {
                        ".": -1.1334871053695679,
                        ",": -1.3366121053695679,
                        " when": -2.3366122245788574,
                        " in": -2.9381747245788574,
                        "...": -3.3287997245788574,
                        " and": -3.3912997245788574
                    },
                    {
                        " I": -0.9554294943809509,
                        " the": -1.7679295539855957,
                        " a": -2.2366795539855957,
                        " all": -3.1898045539855957,
                        " we": -3.4241795539855957,
                        " there": -4.322617053985596
                    },
                    {
                        " was": -0.3532562553882599,
                        " were": -1.6813812255859375,
                        " I": -4.0251312255859375,
                        " wasn": -4.1345062255859375,
                        " had": -4.1970062255859375
                    },
                    {
                        " a": -0.3719903528690338,
                        " no": -1.7001153230667114,
                        " an": -3.614177942276001,
                        " this": -4.129802703857422,
                        " nothing": -4.184490203857422
                    },
                    {
                        " electricity": -1.3433531522750854,
                        " one": -1.6949156522750854,
                        " moon": -2.187103271484375,
                        " way": -3.038665771484375,
                        " sign": -3.054290771484375
                    },
                    {
                        ".": -0.8495846390724182,
                        " to": -2.1386470794677734,
                        " in": -2.2870845794677734,
                        ",": -2.4667720794677734,
                        ".\n": -3.2714595794677734
                    }
                ]
            },
            "text": " and there was no moon,",
            "tokens": null
        }
    ],
    "created": 1769297019,
    "model": "gpt-oss-120b",
    "object": "text_completion",
    "system_fingerprint": "fp_feb5e1faa8274e54bef0",
    "time_info": {
        "completion_time": 0.002412253,
        "prompt_time": 0.000347391,
        "queue_time": 0.000245702,
        "total_time": 0.004331350326538086,
        "created": 1769297019.2632425
    },
    "usage": {
        "completion_tokens": 6,
        "prompt_tokens": 8,
        "prompt_tokens_details": {
            "cached_tokens": 0
        },
        "total_tokens": 14
    }
}