Analysis Summary
Gemini 2.5 Pro Preview 06-05 is a broad multimodal Google model supporting text, images, files, and audio within a 1M-token context window. Its coding and live coding results are strong, and tool use and function calling extend it into agentic workflows. The model is well positioned for complex technical and document-heavy tasks.
Suitable workloads include codebase review, software assistance, multimodal research, long-form content planning, and structured client operations that require external actions. Premium output pricing makes it a poor default for bulk copy or routine classification, while the preview label calls for deployment testing around consistency and latency. It is more capable technically than its general intelligence measurement alone suggests.
Adopt it for demanding engineering and analysis workflows, with a lower-cost tier for high-volume generation.
Assessed August 9, 2026
Editorial notes
Gemini 2.5 Pro Preview 06-05 combines strong coding with a million-token multimodal context and broad file, audio, and tool support. Premium output pricing and preview status make it best for demanding, high-value workflows.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
Gemini 2.5 Pro Preview 06-05 combines strong coding with a million-token multimodal context and broad file, audio, and tool support. Premium output pricing and preview status make it best for demanding, high-value workflows.
Benchmark scores
Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
23 Intelligence Index·46.7 Coding Index
How Google: Gemini 2.5 Pro Preview 06-05 compares
Google: Gemini 2.5 Pro Preview 06-05 ranks #158 of 428 AI models we track for overall intelligence, #74 of 201 for coding. Its 1M-token context window is larger than 95% of the models we list. At $1.25 per million input tokens it is cheaper than 23% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on content. The pulled-in intelligence corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $1.25 | $0.001250 |
| Output | $10.00 | $0.010000 |
What would Google: Gemini 2.5 Pro Preview 06-05 cost your business?
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A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 715 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Google: Gemini 2.5 Pro Preview 06-05 for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Google: Gemini 2.5 Pro Preview 06-05
Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy..
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Frequently asked questions about Google: Gemini 2.5 Pro Preview 06-05
How much does Google: Gemini 2.5 Pro Preview 06-05 cost?
Google: Gemini 2.5 Pro Preview 06-05 costs $1.25 per million input tokens and $10.00 per million output tokens.
What is the context window of Google: Gemini 2.5 Pro Preview 06-05?
Google: Gemini 2.5 Pro Preview 06-05 has a context window of 1,048,576 tokens (1M).
Is Google: Gemini 2.5 Pro Preview 06-05 good for coding?
On our coding benchmark index, Google: Gemini 2.5 Pro Preview 06-05 ranks #74 of 201 models, placing it in the broader range of the field for code generation and debugging.
What can Google: Gemini 2.5 Pro Preview 06-05 do?
Google: Gemini 2.5 Pro Preview 06-05 supports image/vision input, tool use, and function calling.
Who created Google: Gemini 2.5 Pro Preview 06-05?
Google: Gemini 2.5 Pro Preview 06-05 is developed by Google and was released on June 5, 2025.
Data sourced from the OpenRouter API, Artificial Analysis, the Hugging Face Open LLM Leaderboard and our own internal testing. Scores are editorially curated by our team.
Last updated: August 24, 2026 8:38 pm