Chat With Multiple AI Models: GPT-4o, Claude 4, Gemini 2.5 Compared

For two years the default question was which AI chatbot to subscribe to. That question is closing. A flat $20 a month now buys a routing layer over GPT-4o, Claude Opus 4, and Gemini 2.5 Pro, plus a hundred smaller models, and the workflow that wins is not loyalty to one vendor but a clean handoff between three for the tasks each actually leads.

The pitch sells itself. The trade-offs do not show up on the marketing page: thinner memory across sessions, weaker native tool use, and a privacy surface that quietly bypasses the zero-retention contracts each vendor signs with paying customers.

Why a Single AI Subscription No Longer Fits

A year ago, picking ChatGPT or Claude was a one-time decision a knowledge worker stopped revisiting. That logic broke once published benchmarks began showing the same model winning one task and losing badly on the next.

Anthropic’s Claude Opus 4 launch documentation reports a 72.5% score on SWE-bench Verified, the coding benchmark that has become the industry’s headline number for software-engineering ability. Google’s Gemini 2.5 Pro runs a 1,048,576-token context window, more than five times what Anthropic’s flagship offers, with native input for video and audio that no other major model matches. OpenAI’s GPT-4o remains the broad generalist with the deepest tool stack and by far the largest installed user base.

No single vendor tops every column. A writer who codes on the side, drafts marketing copy, and analyses three-hour earnings call transcripts is paying for three different sweet spots. The aggregator pitch is that one monthly bill reaches all of them, switching mid-thread without re-uploading context or losing the prompt history.

The reason that pitch has traction now is arithmetic. A separate ChatGPT Plus, Claude Pro, and Gemini Advanced subscription runs $60 a month for one person whose actual usage rarely hits any single tier’s ceiling. Routing the same dollars through one platform that fans out to all three is a real saving for any user whose workload spans more than one specialty.

What Each Top Model Wins in 2026

The cleanest way to think about model choice is by task, not by brand. The three flagships diverge most sharply on context window, native input types, and per-token cost, and those three axes drive almost every routing decision.

GPT-4o: The Default Generalist

OpenAI’s flagship is the broadest, not the deepest. Its strength is the surrounding stack: voice mode, native image generation, Custom GPTs, code interpreter, and the largest plug-in catalogue of any chat product. For ambiguous prompts that mix research, drafting, and a quick calculation, GPT-4o still produces the most predictable output of the three. It is the model new users should start with and the one most aggregators set as default.

Claude Opus 4: The Coding Workhorse

Anthropic released the model on May 22, 2025, and pitched it as a hybrid reasoner that alternates between near-instant responses and extended-thinking passes. The 200,000-token window and high coding-benchmark scores make it the routing pick for any task that touches a real codebase, a multi-file refactor, or a long-form contract analysis. The cost is the headline drawback, at five times Sonnet’s per-token rate.

Gemini 2.5 Pro: The Long-Context Lead

Google’s flagship is the only major model that natively ingests long-form video and full audio recordings without preprocessing. The million-token context window, documented on Google’s official Gemini API pricing page, is the practical advantage for users who feed in entire books, recorded meetings, or full repositories. Pricing tiers up above the 200,000-token threshold, so the headline rate is not the rate most heavy users actually pay.

How Multi-Model Chat Platforms Stitch the Stack Together

An aggregator is, at the engineering layer, a thin client that wraps the vendors’ published APIs. The user types a prompt in one interface, picks a model from a dropdown, and the aggregator forwards the call to OpenAI, Anthropic, or Google over their paid API endpoints. The platform’s value comes from what sits around the forwarding step.

Three pieces of plumbing distinguish a real aggregator from a wrapper:

• Unified billing that meters per-token consumption against one monthly cap rather than three separate vendor invoices, with a fallback to overage credits when the cap fills.
• Cross-model conversation memory that keeps the thread coherent when the user switches from GPT-4o to Claude mid-conversation, by passing the prior turns as context on each new model’s first message.
• Routing logic that either lets the user pick manually or auto-selects a cheaper model for simple turns and reserves the expensive flagships for prompts that genuinely need them.

The trade-off is that none of this is free of friction. Token counts inflate every time context is re-sent to a new model, so the bills creep up faster than a single-vendor subscription would. And the aggregator has no way to invoke a vendor’s proprietary features such as ChatGPT memory, Claude Projects, or Gemini Gems unless the vendor exposes them through the API, which most do not.

Poe, OpenRouter, and Perplexity Compared

The aggregator market has split into three shapes, each optimised for a different buyer.

Poe: The Consumer Aggregator

Quora’s Poe is the closest thing to a one-stop chat surface that a non-technical user can sign into and immediately use. The interface mirrors ChatGPT’s layout, the model picker is a single dropdown, and the Pro tier bundles a monthly token quota across all the flagship models. Power users build custom bots on top of a base model and share them inside the platform’s catalogue, which has become Poe’s distinct moat.

OpenRouter: The Developer Pipe

OpenRouter is not really a chat product. It is a billing and routing API that exposes one unified endpoint over hundreds of underlying models, including Perplexity’s hosted search models and the full Anthropic and Google catalogues. Developers building production apps pay per token at near pass-through rates, with no monthly minimum. The web chat interface exists but is a side feature.

Perplexity: The Search-First Aggregator

Perplexity’s Pro tier offers a different value: search-grounded answers with citations, layered over a model picker that lets paying users swap between GPT-4o, Claude Sonnet, and Gemini for the response generation step. The model breadth is narrower than Poe’s, but the retrieval and source linking on top of the chat layer is something the standalone vendors do not match.

The Privacy Surface Aggregators Open

Every aggregator sits between the user and the model vendor. That means user prompts route through the aggregator’s servers, get logged or cached at that layer, and then forward to OpenAI, Anthropic, or Google through the aggregator’s API key, not the user’s.

For an individual asking general questions, the surface is no worse than any cloud product. For an enterprise user who would otherwise sign a zero data retention contract with OpenAI or a HIPAA business associate agreement with Anthropic, the aggregator is a problem the privacy team will catch in review.

LLM ecosystems collect and retain more user data than many users realize, with opt-out controls often buried or ineffective, and some services storing user data for several years.

That summary, from a Help Net Security write-up of recent LLM privacy research, applies with extra force when an aggregator inserts itself in the call chain. The vendor’s zero-retention setting does not propagate up to the aggregator, and the aggregator’s terms of service govern what happens to the prompt in transit. Reading those terms is the work most users skip.

Where Native Apps Still Beat the Aggregator

The aggregator pitch wins on cost and breadth. It loses on depth. Five features only the native apps deliver are the reason most heavy users still keep at least one vendor subscription alongside their aggregator account:

• Long-term memory across conversations. ChatGPT memory, Claude Projects, and Gemini Gems each persist context, instructions, and uploaded files across sessions in ways the aggregator’s stitched-together context window cannot reproduce.
• Voice mode with low-latency two-way audio. OpenAI’s Advanced Voice and Google’s Live mode are not exposed through the API, so no aggregator delivers them.
• Native file analysis depth that runs vendor-specific code interpreters, including ChatGPT’s Python sandbox and Claude’s analysis tool, with file persistence across the conversation.
• Vendor-side safety review for prompts the API rejects but the consumer chat surface handles with softer rails, particularly around health and policy questions.
• Direct customer support when something breaks. Aggregators triage to the vendor and add a hop, which can stretch a refund or quota issue from hours into days.

The realistic stack for a serious user in 2026 is one native subscription to the model they live in, paired with an aggregator account for everything else. The combined bill is still less than three native subscriptions, and the workflow keeps each model where it performs best.

Frequently Asked Questions

Can I use GPT-4o, Claude 4, and Gemini 2.5 with a single subscription?

Yes, through an aggregator such as Poe Pro or by paying per token through OpenRouter. Both platforms forward your prompt to the chosen vendor’s API and return the response in one chat interface. The trade-off is that aggregators rarely expose proprietary features such as memory, voice mode, or vendor-side file persistence.

Is a multi-model chat platform safe for sensitive work data?

No, not by default. Your prompts pass through the aggregator’s servers before reaching the model vendor, and the vendor’s zero-retention or enterprise data protections do not extend up the chain unless the aggregator has its own equivalent contract. Sensitive work should go through a direct enterprise account with the vendor, or through a self-hosted deployment.

Which AI model is best for coding right now?

Claude Opus 4 leads the public coding benchmarks, including SWE-bench Verified at 72.5% as published in Anthropic’s launch evaluation. Gemini 2.5 Pro is competitive on multi-file refactors thanks to its million-token context window. GPT-4o remains the strongest at quick, conversational code help.

How is OpenRouter different from Poe?

OpenRouter is a developer API priced per token, with no flat monthly fee, designed for engineers wiring AI into their own apps. Poe is a consumer chat interface with a $19.99 monthly subscription that bundles token quotas across more than a hundred models. Both forward calls to the same vendors but target different buyers.

Do aggregators support voice mode or image generation?

Voice mode is generally not available through aggregators, because OpenAI and Google do not expose their voice features through the public API. Image generation is supported when the underlying vendor offers it through the API, including OpenAI’s image models and Google’s Imagen line, but the user experience is more basic than the native app.

Are aggregator subscriptions worth it if I only use one model?

Probably not. A single-vendor subscription gives you memory, voice, file persistence, and the vendor’s most polished interface for $20 a month. Aggregators win when you regularly route work across at least two of GPT-4o, Claude Opus 4, and Gemini 2.5 Pro, and want one bill instead of three.

For most readers the right move is to subscribe to one native app for the model they live in, then pay an aggregator the second twenty dollars to reach the other two when the task demands it.