Skip to main content
DeepInfra exposes an Anthropic-compatible Messages API. This means tools that target the Anthropic API — Claude Code, the Anthropic Python and TypeScript SDKs, and any framework with an Anthropic adapter — can point at DeepInfra and use open-source models.

​
Endpoint

https://api.deepinfra.com/anthropic
Two endpoints are available:
EndpointDescription
POST /anthropic/v1/messagesCreate a message (chat completion)
POST /anthropic/v1/messages/count_tokensCount tokens for a message request

​
Authentication

Both standard Anthropic authentication methods are supported:
HeaderExample
AuthorizationBearer $DEEPINFRA_TOKEN
x-api-key$DEEPINFRA_TOKEN
You can also pass anthropic-version and anthropic-beta headers as needed.

​
Using the Anthropic SDK

pip install anthropic

import anthropic

client = anthropic.Anthropic(
    base_url="https://api.deepinfra.com/anthropic",
    api_key="$DEEPINFRA_TOKEN",
)

message = client.messages.create(
    model="deepseek-ai/DeepSeek-V3",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello!"}
    ],
)

print(message.content[0].text)

​
Using with Claude Code

Claude Code can use DeepInfra as its backend. To keep your normal Claude Code setup untouched, add a dedicated shell function to your ~/.bashrc or ~/.zshrc: 
deepinfra() {
  export ANTHROPIC_BASE_URL=https://api.deepinfra.com/anthropic
  export ANTHROPIC_AUTH_TOKEN=$DEEPINFRA_TOKEN
  export ANTHROPIC_MODEL=deepseek-ai/DeepSeek-V3.1-Terminus
  export ANTHROPIC_SMALL_FAST_MODEL=Qwen/Qwen3-30B-A3B
  export CLAUDE_CODE_MAX_OUTPUT_TOKENS=16384
  claude "$@"
}
Then run deepinfra instead of claude to launch Claude Code via DeepInfra. Your regular claude command stays unchanged.
ANTHROPIC_SMALL_FAST_MODEL is used for lightweight tasks like tab completions and commit messages. Pick a fast, cheap model here to keep costs low.

​
Streaming

Streaming works the same as the Anthropic API — use stream=True (Python) or stream: true (JS/cURL): 
with client.messages.stream(
    model="deepseek-ai/DeepSeek-V3",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Write a short poem about open source."}],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

​
Token counting

Count the tokens in a message request before sending it: 
curl "https://api.deepinfra.com/anthropic/v1/messages/count_tokens" \
  -H "Content-Type: application/json" \
  -H "x-api-key: $DEEPINFRA_TOKEN" \
  -d '{
      "model": "deepseek-ai/DeepSeek-V3",
      "messages": [
        {
          "role": "user",
          "content": "Hello, how are you?"
        }
      ]
    }'

​
Notes

  • You are running open-source models via the Anthropic protocol, not Anthropic’s Claude models.
  • Model names use DeepInfra identifiers (e.g. deepseek-ai/DeepSeek-V3), not Anthropic model names.
  • Not all Anthropic-specific features may be supported. Standard message creation, streaming, and token counting work as expected.

Chat Completions

Use the OpenAI-compatible API instead.

Authentication

API keys and scoped JWTs.