GPT-5.4-mini

LiteLLM now supports GPT-5.4-mini and GPT-5.4-nano — cost-effective models for simple completions and high-throughput workloads.

:::note If you're on v1.82.3-stable or above, you don't need any update to use these models. :::

Usage

1. Setup config.yaml

model_list:
  - model_name: gpt-5.4-mini
    litellm_params:
      model: openai/gpt-5.4-mini
      api_key: os.environ/OPENAI_API_KEY
  - model_name: gpt-5.4-nano
    litellm_params:
      model: openai/gpt-5.4-nano
      api_key: os.environ/OPENAI_API_KEY

2. Start the proxy

litellm --config /path/to/config.yaml

3. Test it

# GPT-5.4-mini
curl -X POST "http://localhost:4000/v1/chat/completions" \\
  -H "Content-Type: application/json" \\
  -H "Authorization: Bearer $LITELLM_KEY" \\
  -d '{
    "model": "gpt-5.4-mini",
    "messages": [{"role": "user", "content": "What is the capital of France?"}]
  }'

# GPT-5.4-nano
curl -X POST "http://localhost:4000/v1/chat/completions" \\
  -H "Content-Type: application/json" \\
  -H "Authorization: Bearer $LITELLM_KEY" \\
  -d '{
    "model": "gpt-5.4-nano",
    "messages": [{"role": "user", "content": "What is 2 + 2?"}]
  }'

from litellm import completion

# GPT-5.4-mini
response = completion(
    model="openai/gpt-5.4-mini",
    messages=[{"role": "user", "content": "What is the capital of France?"}],
)
print(response.choices[0].message.content)

# GPT-5.4-nano
response = completion(
    model="openai/gpt-5.4-nano",
    messages=[{"role": "user", "content": "What is 2 + 2?"}],
)
print(response.choices[0].message.content)

Notes

• Both models support function calling, vision, and tool-use — see the OpenAI provider docs for advanced usage.
• GPT-5.4-nano is the most cost-effective option for simple tasks; GPT-5.4-mini offers a balance of speed and capability.