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Evaluation Models

DeepSeek

deepeval allows you to use deepseek-chat and deepseek-reasoner directly from DeepSeek to run all of deepeval's metrics, which can be set through the CLI or in python.

Command Line

To configure your DeepSeek model through the CLI, run the following command:

deepeval set-deepseek --model=deepseek-chat \
    --temperature=0

The CLI command above sets deepseek-chat as the default model for all metrics, unless overridden in Python code. To use a different default model provider, you must first unset DeepSeek:

deepeval unset-deepseek

Python

You can also specify your model directly in code using DeepSeekModel.

from deepeval.models import DeepSeekModel
from deepeval.metrics import AnswerRelevancyMetric

model = DeepSeekModel(
    model="deepseek-chat",
    api_key="your-api-key",
    temperature=0
)

answer_relevancy = AnswerRelevancyMetric(model=model)

To use any DeepSeek model directly in deepeval, set the USE_DEEPSEEK_MODEL=1 in your env and simply pass the name of your desired model in your metric initialization:

from deepeval.metrics import AnswerRelevancyMetric

answer_relevancy = AnswerRelevancyMetric(
    model="deepseek-chat",
)

You should also set the other necessary vars like DEEPSEEK_API_KEY to be able to use the Deepseek models as shown above.

There are ZERO mandatory and SIX optional parameters when creating a DeepSeekModel:

  • [Optional] model: A string specifying the name of the DeepSeek model to use. Defaults to DEEPSEEK_MODEL_NAME if not passed; raises an error at runtime if unset.
  • [Optional] api_key: A string specifying your DeepSeek API key for authentication. Defaults to DEEPSEEK_API_KEY if not passed; raises an error at runtime if unset.
  • [Optional] temperature: A float specifying the model temperature. Defaults to TEMPERATURE if not passed; falls back to 0.0 if unset.
  • [Optional] cost_per_input_token: A float specifying the cost for each input token for the provided model. Defaults to DEEPSEEK_COST_PER_INPUT_TOKEN if available in deepeval's model cost registry, else None.
  • [Optional] cost_per_output_token: A float specifying the cost for each output token for the provided model. Defaults to DEEPSEEK_COST_PER_OUTPUT_TOKEN if available in deepeval's model cost registry, else None.
  • [Optional] generation_kwargs: A dictionary of additional generation forwarded to the OpenAI chat.completions.create(...) call.

Parameters may be explicitly passed to the model at initialization time, or configured with optional settings. The mandatory parameters are required at runtime, but you can provide them either explicitly as constructor arguments, or via deepeval settings / environment variables (constructor args take precedence). See Environment variables and settings for the DeepSeek-related environment variables.

Available DeepSeek Models

Below is the comprehensive list of available DeepSeek models in deepeval:

  • deepseek-chat
  • deepseek-v3.2
  • deepseek-v3.2-exp
  • deepseek-v3.1
  • deepseek-v3
  • deepseek-reasoner
  • deepseek-r1
  • deepseek-r1-lite
  • deepseek-v2.5
  • deepseek-coder
  • deepseek-coder-6.7b
  • deepseek-coder-33b

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