Gemini Models: All Google Models at a Glance

Google Gemini has established itself as one of the strongest competitors to ChatGPT and Claude since its launch in December 2023.

The evolution is impressive: Starting with the first 1.0 models, then the major 1.5 versions with 2 million token context, up to the current 2.5 models. Each generation has surpassed the previous one.

But which Gemini model is right for your application? What distinguishes Pro from Flash? And how does Gemini compare to ChatGPT and Claude?

In this article, I'll explain everything important about the different Gemini models, their features, prices, and availability.

What are Gemini Models?

Gemini models are Google's advanced Large Language Models developed by DeepMind and Google Research.

What makes Gemini different? A few things stand out immediately:

First: Native multimodality from the start. Google trained Gemini with text, images, audio, and video – not like other providers who patched that in later. This gives Gemini a much deeper understanding of all these modalities together.

Then there's the context window: Gemini 2.5 Pro processes up to 1 million tokens (experimentally even 2 million). That's approximately 700,000 words or over 1,400 book pages. In a single request. That's... very large.

Google also doesn't have a one-model strategy. Instead: Nano for smartphones, Flash for most standard tasks, Pro for demanding stuff. Each has its place. And because Gemini is deeply integrated into Google Search, Workspace, and Android, it works particularly well there.

Google has taken a different approach with Gemini than OpenAI: Instead of focusing on maximum benchmark performance, the focus is on practical versatility, multimodality, and integration into the Google ecosystem.

Comparison of All Gemini Models

Here's a detailed overview of all Gemini models with their key properties:

Gemini 3.0 Pro Preview is the latest generation of Google's AI models and is currently in early access.

Key Features:

• Latest AI generation from Google DeepMind
• Preview access for selected developers and companies
• Improved reasoning capabilities compared to Gemini 2.5
• Multimodal improvements especially in video understanding
• 1 million token context window (input), up to 64,000 tokens output
• Tiered API pricing: $2.00 / $12.00 per million tokens (under 200k context), $4.00 / $18.00 (over 200k context)
• Access via Google AI Studio Early Access Program

Availability: Gemini 3.0 Pro is currently only available as a preview for selected partners. The full public release is expected for early 2026. During the preview phase, Google may offer free API usage for testing purposes.

Gemini 2.5 Pro is Google's current premium variant. It has the highest performance of the entire family – if you need to solve complex tasks, this is your model. (More about the Gemini API in our separate guide.)

What does Pro offer specifically?

• State-of-the-art performance on complex reasoning and code tasks
• 1 million token context window (experimentally also 2 million)
• Tiered pricing: $1.25 / $10 for standard prompts (≤ 128K tokens), $2.50 / $15 for longer ones
• Native multimodality – process text, images, audio, video together
• Prompt caching with 75 % discount on cached inputs ($0.3125 instead of $1.25–2.50)
• API model string: gemini-2.5-pro

What makes Gemini 2.5 Pro special?

Gemini 2.5 Pro is Google's answer to Claude 4 Opus and GPT-4o. It offers comparable performance on complex reasoning tasks and surpasses both competitors in processing very long contexts. The 1 million token window enables analysis of complete books, large codebases, or hours of video transcripts in a single API call.

The tiered pricing structure makes it economical: For most standard prompts (≤ 128K tokens) you pay only $1.25 / $10 – significantly cheaper than Claude 4 Opus ($15 / $75) with comparable performance.

Where can you get it? The Google AI API, Google AI Studio, Vertex AI, or Google Cloud.

When do you need Pro? When you want to analyze entire codebases, comb through long research papers, summarize thick contracts, or process hours of video in one shot. This isn't meant for chatbots – that's what Flash is for and it's cheaper.

Gemini 2.5 Flash is the balanced variant – the model evergreen of the 2.5 series. It delivers 90 % of Pro performance but costs a fraction and is significantly faster.

The key specs:

• 90 % of Pro performance at a fraction of the cost
• 2–3x faster than Pro (inference speed)
• 1 million token context
• $0.30 input / $2.50 output per million tokens
• Prompt caching: $0.075 for cached inputs
• Multimodal: text, images, audio, video
• API string: gemini-2.5-flash

What makes Gemini 2.5 Flash special?

Gemini 2.5 Flash is the ideal production model for 90 % of all use cases. It offers nearly the same quality as Pro (90 % performance) at 80 % lower cost and 2-3x faster response time. This makes it perfect for chatbots, content generation, and automation workflows where fast responses matter more than absolute highest precision.

Compared to ChatGPT GPT-4o ($15 / $60 per million tokens), Gemini 2.5 Flash offers 98 % cost savings at similar quality – an unbeatable price-performance ratio.

You can find Flash via Google AI API, Google AI Studio, Vertex AI, Google Cloud – and it's the backend model for many Google products.

Specific use cases: Chatbots that need to respond quickly. Content generation (articles, marketing copy, social posts). Data extraction from unstructured sources. Email classification, sentiment analysis, summaries. Screenshot understanding and OCR. For all this, you don't need Pro, Flash is sufficient and saves money.

Gemini 2.5 Flash-Lite is what it says: The cheapest usable LLM on the market. And extremely fast at the same time.

The key numbers:

• $0.10 input / $0.40 output per million tokens (cheapest on the market)
• 5x faster than Pro models
• Still 70–80 % of Flash performance
• 1 million token context
• Prompt caching: $0.025 for cached inputs
• Multimodal: text, images, audio, video
• API string: gemini-2.5-flash-lite

Why is this so interesting? It's 50–60 % cheaper than GPT-4o-mini ($0.15 / $0.60) or Claude 3 Haiku ($0.25 / $1.25). And it's not slow – rather the opposite.

The quality? 70–80 % of Flash performance for chatbot responses, simple text generation, and classification. If you need millions of API calls daily, the cost savings are enormous.

Where can you find it? Google AI API, Google AI Studio, Vertex AI.

Use cases: Chatbots with millions daily. Large-scale content moderation. Sentiment analysis, categorization, tags. Real-time applications where low latency matters. Massive batch processing on a small budget.

Gemini 2.0 Flash is the older version of Flash. The advantage: Free with rate limits.

Quick info:

• 100 % free (rate limits: 15 req./min, 1,500/day, 1M/month)
• ~80 % of 2.5 Flash performance
• 1 million token context
• Multimodal: text, images, audio
• API string: gemini-2.0-flash

Use case: Prototyping, quick tests, low-volume applications. If you really need production without rate limits, upgrade to 2.5 Flash.

Gemini 1.5 Pro was a big deal in 2024: First model with 2 million token context. That was a world record at the time.

Today: It will be shut down on April 30, 2025. If you're still using 1.5 Pro, migrate to 2.5 Pro – better performance, less hassle.

What 1.5 had: 2 million tokens (impressive back then). Native multimodality. Strong video and document analysis. But that was 2024.

Gemini 1.5 Flash was basically the cheaper, faster version of 1.5 Pro. Also deprecated.

The facts: 1 million token context. Fast, low cost. Multimodal. But also going offline on April 30, 2025. Users should switch to 2.5 Flash.

Gemini 1.0 was the first attempt. Today: No longer relevant.

What was it? 32,000 token context. Text-only, no images/videos. Pro was standard, Ultra was premium. Both are long gone. Google quickly replaced them with 1.5 and 2.x – much better models.

Gemini Nano is different: On-device AI for smartphones. Runs locally, no cloud.

What's important:

• On-device: Directly on smartphones, no cloud call
• Two variants: Nano-1 (text-only) and Nano-2 (multimodal)
• 4,000 token context (small, but sufficient for smartphone tasks)
• Privacy: Everything stays local
• Hardware: Pixel smartphones, Samsung Galaxy S24+, other Android devices
• Use cases: Smart reply, live transcription, offline translation, photo editing

Availability: Already integrated in various Android phones. Google rolls it out via system updates. Developers can use the AICore API.

Price Comparison of All Gemini Models

The following table shows a detailed overview of all Gemini prices (all figures in $ per million tokens). For a detailed analysis, we recommend our API cost calculator:

Important notes on the price table:

• Gemini 2.5 Pro has tiered pricing: Lower prices for prompts ≤ 128,000 tokens ($1.25 / $10), higher prices for longer prompts (greater than 128,000 tokens: $2.50 / $15)
• Context caching (prompt caching) enables 75 % discount on cached input tokens with repeated use. Example: Gemini 2.5 Flash input normally costs $0.30, cached only $0.075
• Gemini 2.0 Flash is completely free with rate limits: 15 requests per minute, 1,500 per day, 1 million per month
• Output prices for cached prompts remain the same as standard (no discount on output)