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Completion Request

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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: ""
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model
string
required
Available options:
  • llama3.1-8b
  • llama-3.3-70b
  • qwen-3-32b
  • qwen-3-235b-a22b-instruct-2507 (preview)
  • qwen-3-235b-a22b-thinking-2507 (preview)
  • qwen-3-coder-480b (preview)
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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
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return_raw_tokens
boolean | null
Return raw tokens instead of text.Default: false
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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
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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
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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
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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
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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
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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.Default: 1.0
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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.Default: 1.0
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echo
boolean
Echo back the prompt in addition to the completion. Incompatible with return_raw_tokens=True.Default: false
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user
string | null
A unique identifier representing your end-user, which can help Cerebras to monitor and detect abuse.Default: null
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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.The max value is 20.Default: 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.

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Completion Response

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choices
object[]
required
The list of completion choices the model generated for the input prompt.
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created
integer | null
required
The Unix timestamp (in seconds) of when the completion was created.
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id
string
A unique identifier for the completion.
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model
string
The model used for completion.
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object
string
required
The object type, which is always “text_completion”
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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.
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usage
object
Usage statistics for the completion 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="llama3.1-8b",
    logprobs=5,
)

print(completion)

{
    "id": "chatcmpl-b8718798-d389-4421-9242-13b07e84983b",
    "choices": [
        {
            "finish_reason": "length",
            "index": 0,
            "text": " when I stumbled upon a small, quirky shop tucked away in a quiet alley. The sign above the door read \"Curios and Wonders,\" and the windows were filled with a dazzling array of strange and exotic items. I pushed open the door and stepped inside, my eyes adjusting to the dim light within.\n\nThe shop was a treasure trove of oddities, with shelves upon shelves of peculiar objects that seemed to defy explanation. There were vintage taxidermy animals, antique medical equipment, and",
             "logprobs": {
              "text_offset": [0, 5, 7, 16, 21, 23],
              "token_logprobs": [-0.15, -0.08, -0.22, -0.11, -0.19, -0.05],
              "tokens": [" when", " I", " stumbled", " upon", " a", " small"],
              "top_logprobs": [
                  {
                      " when": -0.15,
                      ",": -1.8,
                      ".": -2.3,
                      " and": -2.9,
                      " as": -3.2
                  },
                  {
                      " I": -0.08,
                      " the": -2.1,
                      " a": -2.7,
                      " she": -3.4,
                      " he": -3.6
                  },
                  {
                      " stumbled": -0.22,
                      " walked": -1.5,
                      " discovered": -2.8,
                      " came": -3.1,
                      " found": -3.5
                  }
                  // ... (remaining tokens omitted for brevity)
               ]
           }
       }
    ],
    "created": 1731597024,
    "model": "llama3.1-8b",
    "system_fingerprint": "fp_e8eacef18a",
    "object": "text_completion",
    "usage": {
        "prompt_tokens": 10,
        "completion_tokens": 100,
        "total_tokens": 110
    },
    "time_info": {
        "queue_time": 4.673e-05,
        "prompt_time": 0.0004940576161616161,
        "completion_time": 0.045957338383838385,
        "total_time": 0.058876991271972656,
        "created": 1731597024
    }
}