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Claude and GPT, One API: A 59API Quick-Start Guide

One integration, two model families

Using Claude and GPT should not require maintaining two completely separate client integrations. A unified API lets your application send requests through one gateway while selecting the model for each task. You keep the connection code stable and change the model identifier when you want a different option.

59API is a low-cost, pay-as-you-go AI API relay with an API base URL of https://api.59api.com. It supports Claude, GPT, Gemini, DeepSeek, and other model families through OpenAI-compatible access. For a concrete starting point, compare Claude Sonnet 5.5 and GPT-6.1 Sol on the same small set of development tasks.

1. Create a key and prepare your environment

Sign up for 59API when you are ready to try a unified setup, then create an API key and check the available balance and current model pricing. Store the key in an environment variable rather than committing it to your repository.

Install the Python client with pip install openai. In a macOS or Linux shell, set your credential with:

export OPENAI_API_KEY='YOUR_59API_KEY'

Despite the variable name, this is your 59API credential, not a key issued by another provider. The SDK accepts it because you will explicitly configure the relay's base URL.

2. Discover the exact model identifiers

Human-readable model names and API identifiers are not necessarily identical. Do not guess an identifier by lowercasing a product name. Check the model listing in your account or request the OpenAI-compatible model catalog:

curl https://api.59api.com/v1/models -H "Authorization: Bearer $OPENAI_API_KEY"

Copy the exact IDs corresponding to your chosen Claude and GPT models, then save them locally:

export CLAUDE_MODEL_ID='EXACT_CLAUDE_ID'; export GPT_MODEL_ID='EXACT_GPT_ID'

If a model is missing or inaccessible, check account availability and the current catalog before debugging your application code.

3. Send your first request

Run the following Python statements in a script or interactive session. The SDK uses the OpenAI-compatible versioned base URL, https://api.59api.com/v1, and handles the chat-completions route itself.

import os; from openai import OpenAI; client = OpenAI(api_key=os.environ['OPENAI_API_KEY'], base_url='https://api.59api.com/v1'); response = client.chat.completions.create(model=os.environ['CLAUDE_MODEL_ID'], messages=[{'role': 'user', 'content': 'Explain three ways to reduce latency in a Python API.'}]); print(response.choices[0].message.content)

To use GPT, keep the same client and request structure, but replace os.environ['CLAUDE_MODEL_ID'] with os.environ['GPT_MODEL_ID']. Your authentication, endpoint configuration, and response-reading code remain unchanged.

4. Compare results before adding routing

Start with a representative test set: one debugging question, one structured extraction task, and one explanation request. Send identical inputs to both models and record:

• Correctness: Does the answer satisfy the task and pass relevant tests?
• Latency: How long does the complete response take?
• Cost: What do actual usage and the applicable rates imply per successful task?

Then choose a default model and make the alternative an explicit application setting. A unified endpoint does not automatically provide intelligent routing or failover; implement those policies deliberately.

5. Keep compatibility and costs predictable

59API offers native, official-quality models without downgrading and positions itself among the cheapest relays. Its pay-as-you-go approach makes small comparisons practical without committing to a subscription. Check current input, output, and any caching rates rather than assuming every model has the same economics. A referral rebate is also available; review its terms separately from API usage pricing.

OpenAI SDK compatibility does not mean every model supports identical tools, structured outputs, reasoning controls, or token-limit parameters. Begin with basic messages, then validate each feature against your selected model. Set application-level usage budgets and avoid repeatedly sending unnecessary conversation history.

6. Add production safeguards

Set timeouts, bound retries for transient failures, and handle rate limits without retrying invalid credentials or malformed requests indefinitely. Log model identifiers, latency, and request IDs when available, but redact keys and sensitive prompts. 59API also supports Claude Code, Codex, and Gemini CLI; those tools need their own configuration rather than automatically inheriting your Python client's settings.

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