Claude vs GPT vs Gemini vs DeepSeek: how to choose an API model in 2026

What the current catalog contains

The live Claudexia response checked on October 4, 2026 included these families:

These are supplier model IDs, not independent claims about official product naming or comparative scores. Check the current models page before pinning one in code.

Compare the work, not the logo

The first candidate is only a starting point. If two models pass, compare latency and token use on the same requests. If one fails, save the failing prompt. That example will be more useful than a vague preference.

A fair evaluation loop

Create 20 to 50 anonymized requests for each important workflow. Give every model the same system rules and the same input. Score the output with a short rubric:

1. Did it answer the requested task?
2. Did it follow the output schema?
3. Did it invent a fact that was not in the input?
4. Did it finish within the allowed time?

Run the set again after changing a model ID or a prompt. Keep model selection separate from prompt editing. Otherwise the comparison has two moving parts.

A provider-neutral client

The route depends on the SDK you use. Claudexia keeps model selection in the request, so your application can make the choice in one place:

const route = {
  review: "claude-opus-5-5",
  support: "claude-sonnet-5",
  extraction: "gpt-6-luna",
  longDocument: "gemini-3.1-pro",
  codingExperiment: "deepseek-v4.1-flash",
} as const;

const result = await client.responses.create({
  model: route[task],
  input: prompt,
});

Use the request format supported by your selected client. Keep a model adapter at the boundary if your app calls Anthropic Messages, OpenAI-compatible chat, or another protocol.

Where a single provider helps

Four vendor accounts make experiments harder to reproduce. Keys, billing views, rate limits, and logging all differ. A single gateway gives your router one authentication boundary and one place to record model ID, latency, and token counts.

It does not remove the need to read model documentation. Confirm request shape, context limits, streaming support, and error handling for every route. A shared endpoint simplifies operations. It does not make different models interchangeable in every detail.

Practical routing rules

Use a strong model for the first pass on a high-risk task, then use a smaller model for deterministic follow-up work. Do not send personal data or secrets to a model unless your data policy explicitly allows it. Redact before the request and log identifiers rather than full prompts.

Set a timeout and a retry budget. Retries are useful for network errors. A second call rarely fixes a bad instruction, so route that case to a review queue instead.

FAQ

Which family is the best default?

There is no honest universal winner. The best family is the one that passes your task rubric with acceptable latency and operating cost.

Can I compare Claude, GPT, Gemini, and DeepSeek with one key?

The current Claudexia catalog exposes model IDs from these families through one service. Verify access in the live catalog and keep a small fallback route for unavailable IDs.

Should I use a benchmark to choose a model?

Use published benchmarks as background. Make the decision with anonymized examples from your own workflow, because prompt shape and output checks change the result.

Which model should handle a support escalation?

Route the first answer to a model that passes your policy and escalation tests. If the request involves an account action, payment, legal issue, or uncertain policy, send it to a human.

Where are the current model IDs listed?

The models documentation and the API catalog are the sources to check before deployment. Model names in an old article should not override the live response.