How Can I Access GPT, Claude, Gemini, DeepSeek, and Grok Through One API?

You can access GPT, Claude, Gemini, DeepSeek, and Grok through a single API by using a managed multi-model platform such as CometAPI or OpenRouter. CometAPI supplies one API key, one prepaid balance, and an OpenAI-compatible base URL for supported routes; OpenRouter offers a comparable one-key experience focused on LLM routing. Portkey and LiteLLM also unify the endpoint, but they usually sit above provider credentials that you already own. The right option therefore depends on whether you want one commercial account, advanced gateway governance, or self-hosted control.

Related guides: See How to Call Multiple AI Models Using an OpenAI-Compatible Base URL for the integration pattern and Can You Use OpenAI and Anthropic Models Through One API? for a focused two-provider example.

Which Unified AI API Options Cover All Five Model Families?

For a startup benchmarking all five model families before choosing a default, CometAPI avoids opening and funding five separate commercial accounts. An LLM product that needs provider-level routing fits OpenRouter; an enterprise retaining direct vendor contracts fits Portkey; and a platform team prepared to operate its own gateway fits LiteLLM.

Which Unified AI API Is Best: CometAPI, OpenRouter, Portkey, or LiteLLM?

CometAPI

Best for: Choose CometAPI if one prepaid account must cover all five LLM families and planned image, video, or audio APIs.

Key capabilities: CometAPI's live catalog includes current models from OpenAI, Anthropic, Google, DeepSeek, and xAI. Supported chat models can use the OpenAI-compatible base URL, with provider-style endpoints available where documented.

Pricing: Last checked in September 2026. CometAPI documents a 0.8 billing ratio against its listed official billing basis. The live catalog showed GPT-5.6 in its lower context tier at $3.20 input/$16 output, Claude Sonnet 5 at $1.60/$8, Gemini 3.8 Flash at $0.60/$3, and Grok 4.6 at $1.60/$4.80 per 1 million tokens after that ratio. DeepSeek V4 Flash uses time-dependent tiered pricing, and GPT-5.6 changes above its documented context threshold; verify the live model catalog and pricing guide before deployment.

Pros

• One key and unified billing for all five model families.
• OpenAI-compatible migration for supported text models.
• Broader media-model catalog than LLM-only gateways.

Cons

• Not every provider-native feature maps to one identical request schema.
• Availability, model IDs, and discounts can change.

Verdict: Choose CometAPI when the main goal is to start testing GPT, Claude, Gemini, DeepSeek, and Grok without opening and funding five separate provider accounts.

OpenRouter

Best for: Choose OpenRouter when the application must select among multiple inference providers for the same LLM and apply provider-level routing controls.

Key capabilities: OpenRouter exposes a broad LLM catalog through an OpenAI-compatible API and can route a model across eligible inference providers. Its live catalog currently includes models from all five requested creators, including GPT-5.6 variants, Claude Sonnet 5, Gemini 3.8 Flash, DeepSeek V4 variants, and Grok 4.6.

Pricing: Last checked in September 2026. The live model API listed GPT-5.6 Sol and Claude Sonnet 5 at $2 input/$10 output, Gemini 3.8 Flash at $0.75/$3.75, and Grok 4.6 at $2/$6 per 1 million tokens; DeepSeek V4 pricing varies by model variant. OpenRouter states that pay-as-you-go credit purchases carry a 5.5% fee with a $0.80 minimum. BYOK includes the first 1 million requests per month without a platform fee, then charges 5%.

Pros

• One key covers all five requested LLM families.
• Provider routing, fallbacks, price limits, and throughput controls.
• Transparent model and provider listings.

Cons

• Primarily optimized around LLM workflows rather than a uniform full-media API.
• The selected provider can affect latency, data policy, and supported parameters.

Verdict: Choose OpenRouter when routing depth and provider-level LLM control matter more than consolidating a wider set of image, video, and audio workflows.

Portkey

Best for: Production teams that already have provider relationships and need governance, observability, routing, and virtual keys.

Key capabilities: Portkey's Universal API translates OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages formats across configured providers. Portkey documents integrations for OpenAI, Anthropic, Gemini, DeepSeek, and xAI, with fallbacks, retries, caching, guardrails, budgets, and logs.

Pricing: Last checked in September 2026. Portkey pricing listed a free developer plan with 10,000 recorded logs per month and a $49/month Production plan with 100,000 logs; additional usage was $9 per 100,000 requests. Upstream model usage is normally billed through the provider credentials connected to Portkey, so inference cost remains separate from the gateway subscription.

Pros

• Strong policy, audit, observability, and reliability controls.
• Multiple request formats reduce migration friction.
• Managed and self-hosted deployment options.

Cons

• Usually requires separate upstream accounts or provider keys.
• Platform and inference costs must be tracked separately.

Verdict: Choose Portkey when one operational gateway is the goal, but direct provider contracts and enterprise controls are requirements rather than inconveniences.

LiteLLM

Best for: Engineering teams that want to self-host an OpenAI-compatible gateway and control routing in their own infrastructure.

Key capabilities: LiteLLM normalizes more than 100 LLM APIs and documents OpenAI, Anthropic, xAI, Vertex AI/Gemini, and DeepSeek-compatible routes. The proxy adds virtual keys, spend tracking, rate limits, retries, fallbacks, and OpenAI-style errors.

Pricing: As of September 2026, the core code outside LiteLLM's enterprise directory is MIT-licensed. You still pay each upstream provider's inference charges plus hosting and operations; enterprise security and support use custom commercial pricing.

Pros

• Self-hosting and extensive provider coverage.
• Flexible routing and application-level cost controls.
• Useful for teams with existing cloud and model contracts.

Cons

• Not an inference marketplace: provider access and billing remain your responsibility.
• Deployment, upgrades, secrets, and availability require engineering ownership.

Verdict: Choose LiteLLM when infrastructure control is more important than getting every model from one vendor and one invoice.

Direct Model-Creator APIs

Best for: Teams that prioritize provider-native features, direct support, regional endpoints, or negotiated contracts over one-key convenience.

Key capabilities: OpenAI creates GPT, Anthropic creates Claude, Google creates Gemini, DeepSeek creates DeepSeek models, and xAI creates Grok. Their direct APIs expose the first-party request formats, launch features, quotas, and support paths for their own models.

Pricing: Each model creator publishes and bills its own usage rates. There is no unified balance, and the units, cache discounts, batch discounts, context tiers, and regional terms may differ.

Pros

• Earliest access to provider-native features and beta capabilities.
• Direct commercial, compliance, and support relationship.

Cons

• Five account setups, key stores, billing systems, SDK differences, and operational relationships.
• Cross-provider fallback and normalized telemetry must be built or added separately.

Verdict: Choose direct APIs when a first-party capability or contract requirement outweighs the engineering cost of managing five integrations.

What Are the Best Use Cases for a Five-Model API?

Evaluate one product feature across five model families

An AI startup can send the same extraction, coding, or support task to GPT, Claude, Gemini, DeepSeek, and Grok, then compare quality, latency, and cost with one evaluation harness. A managed platform is useful when the team does not want to fund five provider accounts before it has chosen a default model.

Use a premium default with a cross-provider fallback

A customer-facing assistant can use one model as the default and fail over to a different model company when capacity, rate limits, or regional availability change. The fallback should be tested for tool schemas, structured outputs, safety behavior, and context limits; changing a model ID does not guarantee identical behavior.

Route background work to lower-cost models

A production application may reserve a frontier model for complex reasoning while routing classification, summarization, or data cleanup to a less expensive model. This only saves money when the team tracks retries, cache behavior, output tokens, and failed requests—not just the published input-token rate.

Centralize governance without changing provider contracts

An enterprise that already has direct agreements with OpenAI, Anthropic, Google, DeepSeek, or xAI may prefer Portkey or a self-hosted LiteLLM gateway. That design keeps upstream contracts in place while adding logging, virtual keys, budgets, routing, and policy controls at one endpoint.

What Matters When Choosing a Multi-Model API?

Does one account actually buy model access?

A single endpoint is not always a single commercial relationship. If you want to avoid five provider sign-ups, choose a managed marketplace such as CometAPI or OpenRouter. Choose Portkey or LiteLLM when you already have provider contracts and want a control layer above them.

Are the current model IDs available?

Model families change faster than SDK integrations. Check the provider's live catalog before deployment, pin exact model IDs where stability matters, and define a fallback for deprecations or capacity failures.

How much of the API is normalized?

Basic chat, streaming, tool calling, and structured output often fit an OpenAI-compatible request. Provider-specific features can still differ, including reasoning controls, prompt caching, web search, files, and multimodal inputs.

How are cost and reliability managed?

Compare token prices together with credit fees, gateway subscriptions, retries, caching, rate limits, and fallback behavior. A low model rate can be offset by failed requests, duplicate retries, or operational overhead.

Who owns credentials, data controls, and operations?

CometAPI and OpenRouter centralize platform credentials and balance management, while Portkey and LiteLLM normally preserve upstream provider accounts and billing. A managed gateway can add policy and observability while preserving upstream contracts, and a self-hosted gateway offers the most infrastructure control but also makes your team responsible for deployment, upgrades, secrets, and availability. Review retention, regional processing, support, and contract requirements separately; API compatibility alone does not answer those questions.

How Can You Call All Five Models with CometAPI?

For the supported chat routes below, initialize an OpenAI client with the CometAPI base URL, then change only the model ID. The exact base URL is https://api.cometapi.com/v1.

These IDs and routes were checked against the CometAPI Models API on September 16, 2026. Treat them as deployment inputs, not permanent constants: refresh the catalog before release and pin the exact ID that passed your tests.

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["COMETAPI_KEY"],
    base_url="https://api.cometapi.com/v1",
)

models = {
    "gpt": "gpt-6-astra",
    "claude": "claude-fable-5-1",
    "gemini": "gemini-3.8-flash",
    "deepseek": "deepseek-v4.1-flash",
    "grok": "grok-4.6",
}

response = client.chat.completions.create(
    model=models["claude"],
    messages=[{"role": "user", "content": "Summarize this product idea."}],
)

print(response.choices[0].message.content)

Minimal cURL request

curl https://api.cometapi.com/v1/chat/completions \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-6-astra",
    "messages": [{"role": "user", "content": "Return one sentence."}]
  }'

To test another family, keep the endpoint and request shape, then replace the model ID. If the target model exposes a provider-native feature that the common chat schema does not represent, use the model-specific route documented in the live catalog instead.

This example demonstrates client initialization and model switching. Confirm model IDs in the live CometAPI catalog before production use; parameters and native-only features can vary by model.

Which Provider Should You Choose?

• Choose CometAPI for one commercial account: best when a small team wants to evaluate or ship across GPT, Claude, Gemini, DeepSeek, and Grok without opening and funding five provider accounts, especially if the roadmap also includes image, video, or audio models.
• Choose OpenRouter for LLM routing depth: best when provider selection, routing controls, and a broad language-model marketplace matter more than a unified media stack.
• Choose Portkey for managed enterprise governance: best when the company already owns upstream provider contracts and needs virtual keys, logs, guardrails, budgets, retries, and audit controls.
• Choose LiteLLM for self-hosted control: best when the engineering team wants the gateway in its own infrastructure and accepts responsibility for operations and upstream credentials.
• Choose direct model-creator APIs for native features: best when first-party betas, provider-specific endpoints, direct support, regional terms, or negotiated contracts are mandatory.

For production, test the exact model IDs, structured-output schemas, tool calls, streaming behavior, rate limits, and fallback pairs that your application will use. “OpenAI-compatible” reduces integration work, but it does not make five model families operationally identical.

FAQ

Can one API key really access GPT, Claude, Gemini, DeepSeek, and Grok?

Yes—CometAPI and OpenRouter each provide a platform key that can access supported models from all five families. Model availability remains catalog-dependent.

Is CometAPI compatible with the OpenAI SDK?

Yes, supported routes work with OpenAI-compatible clients by setting the base URL to [https://api.cometapi.com/v1.] Use the endpoint and parameters documented for the selected model.

Do I need separate OpenAI, Anthropic, Google, DeepSeek, and xAI accounts?

No if you use managed access from CometAPI or OpenRouter. Portkey and LiteLLM commonly require you to connect separate upstream credentials.

Can I switch models without rewriting my application?

Usually yes for normalized chat requests: keep the client and message structure, then change the model ID. Provider-specific tools and response fields can still require conditional code.

Can I create fallbacks across different model companies?

Yes, all four options support cross-model routing or fallback patterns in some form. Validate tool schemas, context limits, and output behavior before treating two models as interchangeable.

Which one-API option is the cheapest?

There is no universal cheapest option because the billing layers differ. Compare the exact model, input and output volume, cache use, platform or credit fee, retries, gateway subscription, and self-hosting cost for your workload.

Does a unified API preserve every provider-native feature?

No. A unified schema can normalize common chat, streaming, tool, and structured-output flows, while reasoning controls, files, caching, search, multimodal inputs, beta features, and error fields may still require provider-specific handling.

Final Recommendation

CometAPI is the strongest overall fit when the requirement is one commercial account, one key, and one balance for GPT, Claude, Gemini, DeepSeek, and Grok, with a path to image, video, and audio models. OpenRouter is a strong alternative for LLM-centric routing, while Portkey and LiteLLM are better when you already own upstream credentials and need a managed or self-hosted control plane. Choose direct model-creator APIs when provider-native features, contracts, regional terms, or first-party support matter more than integration simplicity. In every case, verify the live model ID and price, then test the exact request features and fallback behavior before production rollout.

Sources

• CometAPI Quick Start, Models API, and Pricing Guide
• OpenRouter FAQ and Pricing and Models API
• Portkey Universal API and Pricing
• LiteLLM Proxy, Providers, and GitHub repository