The best Google model for serious, complex work — especially when you need to fit an entire codebase or document corpus into a single prompt.
92
Coding
78
Writing
91
Research
72
Images
52
Value
97
Long Context
Use this when
Deep reasoning over very long documents, complex codebases, or multimodal inputs where context size is a constraint with other models.
Skip this if
You need fast, low-cost completions at scale — the $10/1M output cost and balanced latency make it a poor fit for high-throughput or real-time applications.
Pricing
$1.25/1M in
$10.00/1M out
→0%since May 2026
Context
1.0M tokens
Speed
Balanced
Gemini 2.5 Prospecs & pricing
Verified Sep 4, 2026 against the AI Gateway catalog
Pricing shown is for prompts under 200K tokens; inputs over 200K tokens are billed at $2.50/1M input and $15/1M output. Gemini 2.5 Pro includes built-in 'thinking' (reasoning) mode which can increase latency and cost further.
Industry-leading 1M token context window — surpasses Claude Sonnet 4.6 and GPT-4o in raw context capacity
Strong coding and multi-step reasoning benchmarks, competitive with o3-mini on structured problem-solving
Genuinely multimodal: handles text, images, audio, and video natively in a single call
Relatively affordable for a frontier-class model at $1.25/$10 per 1M tokens compared to GPT-4o's higher output costs
Weaknesses
Output cost of $10/1M tokens gets expensive fast for high-volume generation tasks
Response latency is noticeably slower than flash-tier models like Gemini 2.0 Flash or GPT-4o mini
Creative writing and nuanced tone control still trails Claude Sonnet 4.6
Real-world use cases
What people actually use Gemini 2.5 Pro for.
Analyzing an entire software repository (~800K tokens) to identify architectural debt and suggest refactors
Summarizing and cross-referencing a 500-page legal or scientific document with precise citations
Building a multimodal pipeline that processes video frames, transcripts, and structured data in one context
How Gemini 2.5 Pro compares
The nearest models people weigh against it, and what actually separates them.
vs Gemini 2.5 Pro Preview 05-06 — Against Gemini 2.5 Pro Preview 05-06 (Google), Gemini 2.5 Pro lands within a few percent on price and answers faster. Which one wins depends on whether context depth or latency is your constraint.
vs Gemini 3.5 Flash — Against Gemini 3.5 Flash (Google), Gemini 2.5 Pro costs about 7% more per token and answers slower. Gemini 3.5 Flash is the one to check first if the price difference matters more than the ceiling.
vs Gemini 3.6 Flash — Against Gemini 3.6 Flash (Google), Gemini 2.5 Pro costs about 60% more per token and answers slower. Gemini 3.6 Flash is the one to check first if the price difference matters more than the ceiling.
Price History
Gemini 2.5 Pro pricing over time
→0% since May 9
87 data points · tracked daily since May 9, 2026
Ready to try it?
Start using Gemini 2.5 Pro
Deep reasoning over very long documents, complex codebases, or multimodal inputs where context size is a constraint with other models.. Start free — no card required.
Gemini 2.5 Pro Preview 05-06 is Google's latest frontier reasoning model featuring a massive 1M token context window and strong multimodal capabilities. It targets developers and researchers needing deep analytical power with competitive pricing relative to its capability tier.
Verdict
The go-to model when you need a frontier brain and a million-token memory, at a price that won't immediately break your budget.
Quality score
86%
Pricing
$1.25/1M in
$10.00/1M out
Speed
Deliberate
2/5 speed
Context
1.0M tokens
This is a preview model (05-06 date suffix indicates a versioned snapshot); Google may deprecate or change it without long notice. Confirm production readiness before building critical pipelines on this endpoint. The 1M context window applies to text and multimodal inputs combined.
Long ContextReasoningMultimodalFrontierPreview
Best for
Complex multi-document analysis, long-context reasoning, and advanced coding tasks where a massive context window is essential.
Google's I/O 2026 headliner — a Flash-tier model that beats Gemini 3.1 Pro on agentic and coding benchmarks while running roughly 4x faster than comparable frontier models.
Verdict
Excellent fast agentic model, superseded by Gemini 3.6 Flash.
Quality score
89%
Pricing
$1.50/1M in
$9.00/1M out
Speed
Fast
4/5 speed
Context
1.0M tokens
Released at Google I/O, May 19, 2026. Batch API half price; context caching $0.15/1M. 65,536-token output limit.
Google's efficiency-focused successor to 3.5 Flash — higher scores on every benchmark Google tested, ~17% fewer output tokens, and cheaper output pricing.
Verdict
Best Gemini for agents — efficiency king with native computer use.
Quality score
90%
Pricing
$0.75/1M in
$3.75/1M out
Speed
Fast
4/5 speed
Context
1.0M tokens
Released July 21, 2026 alongside 3.5 Flash-Lite and the gated 3.5 Flash Cyber. Knowledge cutoff March 2026. Batch $0.75/$3.75; cached input $0.15/1M.
AgenticComputer useEfficientMultimodal1M context
Best for
Cost-efficient long-horizon agents and computer use
Pricing moves, ranking shifts, and capability updates.
New ModelMar 27, 2026
Google: Gemini 2.5 Pro — added to UseRightAI
Google: Gemini 2.5 Pro (Google) is now indexed. The best Google model for serious, complex work — especially when you need to fit an entire codebase or document corpus into a single prompt.
Gemini 2.5 Pro costs $1.25 per million input tokens and $10 per million output tokens on the API, with cached input at $0.125 per million. A month of 10M input and 2M output tokens runs about $32.50 at list price, before any batch or caching discounts.
What is the context window of Gemini 2.5 Pro?
Gemini 2.5 Pro has a 1.0M tokens context window, with up to 66k tokens of output per response. That is the total of prompt plus response the model can hold in one request.
What is the knowledge cutoff of Gemini 2.5 Pro?
Gemini 2.5 Pro's training data runs through January 2025, and the model was released on March 20, 2025. For anything after that date it needs web search or documents in the prompt.
What is Gemini 2.5 Pro best for?
Gemini 2.5 Pro is best for deep reasoning over very long documents, complex codebases, or multimodal inputs where context size is a constraint with other models.. It is a strong fit when that workflow matters more than the tradeoffs around balanced pricing and balanced speed.
When should I avoid Gemini 2.5 Pro?
You need fast, low-cost completions at scale — the $10/1M output cost and balanced latency make it a poor fit for high-throughput or real-time applications.
What is a cheaper alternative to Gemini 2.5 Pro?
Gemini 3.6 Flash (Google) at $0.75/1M/1M input against Gemini 2.5 Pro's $1.25/1M/1M — roughly 60% less per token all in. Best Gemini for agents — efficiency king with native computer use. Compare it first if Gemini 2.5 Pro's pricing is the thing stopping you.
What is a faster alternative to Gemini 2.5 Pro?
Gemini 3.5 Flash — fast against Gemini 2.5 Pro's balanced, with 1.0M tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
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