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Gemini 2.5 Pro Preview 06-05 vs GPT-5.4

Gemini 2.5 Pro Preview 06-05 (2025) and GPT-5.4 (2026) are frontier reasoning models from Google DeepMind and OpenAI. Gemini 2.5 Pro Preview 06-05 ships a 1M-token context window, while GPT-5.4 ships a not-yet-sourced context window. On pricing, Gemini 2.5 Pro Preview 06-05 costs $1.25/1M input tokens versus $2.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Gemini 2.5 Pro Preview 06-05 is ~100% cheaper at $1.25/1M; pay for GPT-5.4 only for coding workflow support.

Specs

Released2025-03-252026-03-05
Context window1M
Parameters
Architecturedecoder onlydecoder only
LicenseUnknownProprietary
Knowledge cutoff-2025-08

Pricing and availability

Gemini 2.5 Pro Preview 06-05GPT-5.4
Input price$1.25/1M tokens$2.5/1M tokens
Output price$10/1M tokens$15/1M tokens
Providers

Capabilities

Gemini 2.5 Pro Preview 06-05GPT-5.4
Vision
Multimodal
Reasoning
Function calling
Tool use
Structured outputs
Code execution

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on multimodal input: GPT-5.4, reasoning mode: GPT-5.4, function calling: GPT-5.4, and tool use: GPT-5.4. Both models share structured outputs and code execution, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

For cost, Gemini 2.5 Pro Preview 06-05 lists $1.25/1M input and $10/1M output tokens, while GPT-5.4 lists $2.5/1M input and $15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemini 2.5 Pro Preview 06-05 lower by about $2.38 per million blended tokens. Availability is 1 providers versus 2, so concentration risk also matters.

Choose Gemini 2.5 Pro Preview 06-05 when coding workflow support and lower input-token cost are central to the workload. Choose GPT-5.4 when coding workflow support and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.

FAQ

Which is cheaper, Gemini 2.5 Pro Preview 06-05 or GPT-5.4?

Gemini 2.5 Pro Preview 06-05 is cheaper on tracked token pricing. Gemini 2.5 Pro Preview 06-05 costs $1.25/1M input and $10/1M output tokens. GPT-5.4 costs $2.5/1M input and $15/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Gemini 2.5 Pro Preview 06-05 or GPT-5.4 open source?

Gemini 2.5 Pro Preview 06-05 is listed under Unknown. GPT-5.4 is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for multimodal input, Gemini 2.5 Pro Preview 06-05 or GPT-5.4?

GPT-5.4 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for reasoning mode, Gemini 2.5 Pro Preview 06-05 or GPT-5.4?

GPT-5.4 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for function calling, Gemini 2.5 Pro Preview 06-05 or GPT-5.4?

GPT-5.4 has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Gemini 2.5 Pro Preview 06-05 and GPT-5.4?

Gemini 2.5 Pro Preview 06-05 is available on OpenRouter. GPT-5.4 is available on OpenAI API and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.