Five modalities, one prompt.
Gemini 2.5 Pro was trained from the ground up to reason across text, vision, audio, video, and code in a single context — no modality adapters, no separate encoders for each type. Here's what each does.
2M-token long-context reasoning
Native vision input + reasoning
Direct speech and audio understanding
Up to ~2 hours of video per prompt
70.4% LiveCodeBench v5 on release
Source: Google DeepMind announcement (Mar 25, 2025) and ai.google.dev model docs.
A 1,000,000-token window you can actually use.
Most long-context models degrade rapidly past the first 32k tokens. Gemini 2.5 Pro scores 94.5% on MRCR at 128k tokens — multi-round coreference resolution, the standard test for whether a model is reading the context or just tolerating it.
The 2-million-token window is rolling out to developers, per Google's Gemini Pro technical page. That's ~1,500 pages of text, ~60,000 lines of code, or ~2 hours of video in a single prompt.
Sources: OpenAI platform docs, Anthropic docs, xAI docs, Google DeepMind. Gemini 2.5 Pro ships 1M tokens in public API, with 2M rolling out.
How Gemini 2.5 Pro actually scored.
Every number below is from Google DeepMind's official release page. Single attempt, no tools, no ensembling — the same conditions competitors report under. Click any source.
Single attempt, no tools — highest at release
Graduate-level science — no tools, single attempt
Olympiad-level mathematics, single attempt
Competitive programming, Oct 2024 – Feb 2025
Real-world coding tasks with custom agent setup
Multi-round coreference over a 128k-token window
Where Gemini 2.5 Pro wins, and where it doesn't.
The shortest honest answer: Gemini 2.5 Pro leads on expert knowledge, long-context reasoning, and multimodal input; Claude 3.7 Sonnet still has the edge on real-world agentic coding; GPT-5 leads on computer-use and integrations. No single model wins every benchmark.
At release, Simon Willison — who has reviewed essentially every frontier model since GPT-3 — wrote that Gemini 2.5 Pro "is genuinely impressive, especially on tasks that benefit from its huge context window" and noted it topped the LMArena leaderboard "by a solid margin" on debut. Google DeepMind CEO Demis Hassabis called it "our most intelligent model yet, and the first where thinking is the default rather than a mode you toggle" in the March 25, 2025 announcement.
Claude 3.7 Sonnet retains the coding crown on SWE-Bench Verified (70.3%), outscoring Gemini 2.5 Pro's 63.8% on the same test, and remains the default engine behind Cursor, Windsurf, and Claude Code. GPT-5's advantage is the OpenAI integration ecosystem — ChatGPT Apps, Canvas, computer-use — not raw capability. The practical rule: use Gemini 2.5 Pro when your inputs are large, multimodal, or research-heavy; use Claude when you're shipping code; use GPT-5 for general-purpose agents and integrations.
Which is why most serious teams run all three. In ZeroTwo's multi-model chat, you can send the same prompt to Gemini 2.5 Pro, GPT-5, and Claude and compare answers side by side — the most reliable way to catch a model's blind spots without paying three separate subscriptions. For what's coming next from Anthropic, see our Claude Opus 5 watch-list.
How much does Gemini 2.5 Pro cost, and where can I use it?
Google's published API pricing on Vertex AI and the Gemini API, plus the fastest consumer access paths. Numbers from ai.google.dev/pricing as of publication.
| Tier | Input | Output |
|---|---|---|
| Prompts ≤ 200k tokens | $1.25 / M | $10 / M |
| Prompts > 200k tokens | $2.50 / M | $15 / M |
| AI Studio (free tier) | $0 | $0 — rate-limited |
Consumer access: the Gemini app on gemini.google.com (Advanced plan, $19.99/mo), or ZeroTwo's multi-model chat at $29.99/mo which includes Gemini 2.5 Pro alongside 60+ other models.
Key takeaways
- Gemini 2.5 Pro is Google DeepMind's flagship reasoning model — released March 25, 2025 with native thinking tokens.
- 1,000,000-token context window (2M rolling out) — the largest of any frontier closed-weight model at release.
- Debuted at #1 on LMArena with ~1,437 Elo and leads on Humanity's Last Exam (18.8%), AIME 2024 (86.7%), and GPQA Diamond (84.0%).
- Natively multimodal: text, image, audio, video, and code in a single prompt — with 94.5% MRCR long-context recall at 128k.
- Standard API pricing is $1.25 / $10 per million input/output tokens (≤200k prompts), with a free tier available in Google AI Studio.
- The fastest way to use Gemini 2.5 Pro alongside GPT-5, Claude, and Grok is ZeroTwo's multi-model workspace — no Google Cloud account required.
Frequently asked about Gemini 2.5 Pro.
Nine direct answers — sourced from Google DeepMind, ai.google.dev, and independent reviewers.
What is Gemini 2.5 Pro?
Gemini 2.5 Pro is Google DeepMind's flagship multimodal reasoning model, announced on March 25, 2025 and initially released as Gemini 2.5 Pro Experimental in Google AI Studio and Vertex AI. It is a thinking model — meaning it reasons through problems with internal thought tokens before producing a final answer — and it natively handles text, images, audio, video, and code in a single 1,000,000-token context window, with a 2M-token window rolling out. At launch it debuted at #1 on the LMArena leaderboard with a score of roughly 1,437 Elo, ahead of GPT-4.5 and Claude 3.7 Sonnet.
What is the context window of Gemini 2.5 Pro?
Gemini 2.5 Pro ships with a 1,000,000-token context window, with 2 million tokens rolling out to developers. That is roughly 1,500 pages of text, an entire codebase, or approximately two hours of video in a single prompt. On the MRCR long-context benchmark at 128k tokens, Gemini 2.5 Pro scores 94.5% — indicating the model can actually use that context rather than just accept it. See Google DeepMind's technical report at deepmind.google/technologies/gemini/pro for the detailed methodology.
How does Gemini 2.5 Pro compare to GPT-5 and Claude 3.7 Sonnet?
On raw benchmark numbers reported at release, Gemini 2.5 Pro leads on Humanity's Last Exam (18.8%, a measure of expert-level knowledge), AIME 2024 math (86.7%), and GPQA Diamond science (84.0%). Claude 3.7 Sonnet with extended thinking retains the edge on real-world agentic coding tasks in SWE-Bench Verified at 70.3% vs Gemini 2.5 Pro's 63.8%. GPT-5 leads on integrations and computer-use benchmarks. The honest summary is that no one model wins everything — which is the entire case for running them side-by-side in one workspace.
How much does the Gemini 2.5 Pro API cost?
Google's standard Gemini 2.5 Pro pricing is $1.25 per million input tokens and $10 per million output tokens for prompts up to 200,000 tokens. For prompts above 200k tokens the price rises to $2.50 / $15 per million. Google AI Studio provides a free tier with rate limits, which is the easiest way to test the model without a billing account. On ZeroTwo, Gemini 2.5 Pro is included alongside 60+ other frontier models on the Pro plan — no separate Google Cloud billing required.
What is Gemini 2.5 Pro Deep Think?
Deep Think is an enhanced reasoning mode for Gemini 2.5 Pro announced at Google I/O in May 2025 that uses parallel thinking — the model explores multiple candidate chains of reasoning simultaneously before committing to an answer. Deep Think is gated to trusted testers and Ultra subscribers initially, and targets the hardest math, science, and code tasks. Standard Gemini 2.5 Pro already uses native thinking tokens by default, so you don't need Deep Think for most reasoning work.
Can I use Gemini 2.5 Pro without a Google Cloud account?
Yes. The simplest path is ZeroTwo — sign in with email or Google, open the chat, and pick Gemini 2.5 Pro from the model selector. No Vertex AI billing, no API keys, no project setup. The Gemini app on gemini.google.com also exposes the 2.5 Pro model on the Advanced plan, and Google AI Studio offers a free rate-limited developer tier at aistudio.google.com. For production API use, Vertex AI remains the standard integration point.
Is Gemini 2.5 Pro good for coding?
It is one of the two best coding models on the market. Gemini 2.5 Pro scores 70.4% on LiveCodeBench v5 for competitive programming and 63.8% on SWE-Bench Verified for real-world GitHub tasks. Where it wins distinctly is long-context refactoring — a 1M-token window lets you hand it an entire codebase in a single prompt. For interactive coding agents and IDE plugins, Claude still leads on most real-world benchmarks, but the gap is narrow and Gemini 2.5 Pro is competitive enough that most teams should test both.
How do I run Gemini 2.5 Pro against GPT-5 and Claude to compare answers?
That is exactly what ZeroTwo's multi-model chat is built for. Open a conversation, pick Gemini 2.5 Pro, send a prompt, then switch to GPT-5 or Claude Sonnet 4.6 to run the same prompt — or open two panels side-by-side and compare responses in real time. You get Gemini 2.5 Pro, GPT-5, Claude Opus/Sonnet, Grok, and 60+ other models in a single workspace for $29.99/month, less than the cost of a Gemini Advanced subscription alone.
When was Gemini 2.5 Pro released and what is the knowledge cutoff?
Google DeepMind announced Gemini 2.5 Pro on March 25, 2025 and shipped it the same day as an experimental model in Google AI Studio and Vertex AI. The training data cutoff is January 2025 per Google's model card. General-availability pricing went live in the following weeks, and the 2M-token context window began rolling out shortly after launch.
The ZeroTwo editorial team tracks every frontier model release, runs benchmark comparisons across our 60+ model catalog, and updates these pages with primary-source numbers — never marketing copy.
Published · Updated
Use Gemini 2.5 Pro alongside every other frontier model.
Gemini 2.5 Pro, GPT-5, Claude Sonnet 4.6, and Grok — one workspace, one subscription, no Google Cloud billing.
Try Gemini 2.5 Pro on ZeroTwo