Google vs OpenAI: Token Pricing, Speed & Intelligence
Full comparison of Google and OpenAI — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
Gemini 2.5 — the largest context window at the lowest frontier price
Google DeepMind's Gemini family offers some of the most competitive frontier pricing, with Gemini 2.5 Pro delivering top-tier intelligence at $1.25/1M input tokens. The 1M+ token context window is the largest available. Gemini 2.5 Flash is a standout efficient model for vision and multimodal tasks.
OpenAI
GPT-4o, o3, and the world's most widely-used AI API
OpenAI is the creator of the GPT model family and the ChatGPT product. Their API provides access to frontier models including GPT-4o, the o-series reasoning models, and the GPT-4.1 long-context family. Pricing is competitive for frontier-tier capability, with prompt caching available on most models.
Key metrics
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Live token pricing
Strengths & weaknesses
OpenAI
Key differentiators
Frequently asked questions
Google FAQs
How much does the Google Gemini API cost?
Gemini 2.5 Pro costs $1.25/1M input tokens (up to 200K context) and $10/1M output. Gemini 2.5 Flash is $0.15/$0.60 per 1M tokens. Gemini 2.0 Flash is even cheaper at $0.10/$0.40 per 1M tokens.
What is the context window for Gemini models?
Gemini 2.5 Pro and Flash both support a 1,048,576-token (1M+) context window — the largest available from any major LLM provider. This makes them ideal for processing entire codebases, books, or long document collections.
Does Gemini support vision and multimodal inputs?
Yes. All Gemini 2.x models natively support images, audio, and video inputs alongside text. Gemini 2.5 Flash is particularly strong for vision tasks at a low cost.
OpenAI FAQs
How much does the OpenAI API cost?
GPT-4o costs $2.50/1M input tokens and $10/1M output tokens. GPT-4o-mini is $0.15/$0.60 per 1M tokens. Prompt caching cuts input costs by 50% on eligible requests.
What is the difference between GPT-4o and o3?
GPT-4o is a fast, multimodal model optimised for chat, vision, and coding. o3 is a reasoning model that uses chain-of-thought to solve complex problems — it is slower and more expensive but significantly more capable on math, science, and hard coding tasks.
Does OpenAI support prompt caching?
Yes. Prompt caching is available on GPT-4o, GPT-4.1, o3, and o4-mini. Cached input tokens are billed at 50% of the standard input price, making long-context and repeated-system-prompt workloads significantly cheaper.
Provider resources
Google — Gemini 2.5 — the largest context window at the lowest frontier price
Google DeepMind's Gemini family offers some of the most competitive frontier pricing, with Gemini 2.5 Pro delivering top-tier intelligence at $1.25/1M input tokens. The 1M+ token context window is the largest available. Gemini 2.5 Flash is a standout efficient model for vision and multimodal tasks.
Gemini 2.5 Pro delivers frontier-tier intelligence at $1.25/1M input tokens — the best price-to-performance ratio among all frontier models.
OpenAI — GPT-4o, o3, and the world's most widely-used AI API
OpenAI is the creator of the GPT model family and the ChatGPT product. Their API provides access to frontier models including GPT-4o, the o-series reasoning models, and the GPT-4.1 long-context family. Pricing is competitive for frontier-tier capability, with prompt caching available on most models.
The most widely-integrated LLM API — virtually every AI framework and tool supports OpenAI natively.
Key strengths compared
- ▸1M+ token context window — largest available
- ▸Best price-per-intelligence at frontier tier ($1.25/1M input)
- ▸Native multimodal: text, image, audio, video
OpenAI
- ▸Largest ecosystem & third-party integrations
- ▸Best-in-class function calling & structured outputs
- ▸Prompt caching on all major models
Provider category context
Google is a frontier lab, founded in 1998. OpenAI is a frontier lab, founded in 2015. Both are frontier lab providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both Google and OpenAI are frontier labs with proprietary models. Choose based on benchmark performance for your specific task: Google leads on 1m+ token context window — largest available, while OpenAI leads on largest ecosystem & third-party integrations. For cost-sensitive workloads, compare the cheapest model tier from each provider in the pricing table above — the gap between efficient-tier models is often larger than between flagship models.