Enhanced reasoning
State-of-the-art in key math and science benchmarks.
Gemini 2.5 Pro
Best for coding and highly complex tasks
Gemini 2.5 Pro is our most advanced model yet, excelling at coding and complex prompts.
Pro performance
2.5 Pro excels at creating compelling web apps and agentic code applications, along with code transformation and editing.
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Advanced coding
Easily generate code for web development tasks.
Natively multimodal
Understands input across text, audio, images and video.
Long context
Explore vast datasets with a 1-million token context window.
Native audio
Converse in more expressive ways with native audio outputs that capture the subtle nuances of how we speak. Seamlessly switch between 24 languages, all with the same voice.
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Natural conversation
Remarkable quality, more appropriate expressivity, and prosody, delivered with low latency so you can converse fluidly.
Style control
Use natural language prompts to adapt the delivery within the conversation, steer it to adopt accents and produce a range of tones and expressions.
Tool integration
Gemini 2.5 can use tools and function calling during dialog allowing it to incorporate real-time information or use custom developer-built tools.
Conversation context awareness
Our system is trained to discern and disregard background speech, ambient conversations and other irrelevant audio.
Vibe-coding nature with 2.5 Pro
Images transformed into code-based representations of its natural behavior.
Hands-on with 2.5 Pro
See how Gemini 2.5 Pro uses its reasoning capabilities to create interactive simulations and do advanced coding.
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Code a fractal visualization
See how Gemini 2.5 Pro creates a simulation of intricate fractal patterns to explore a Mandelbrot set.
Make an interactive animation
See how Gemini 2.5 Pro uses its reasoning capabilities to create an interactive animation of “cosmic fish” with a simple prompt.
Create your own dinosaur game
Watch Gemini 2.5 Pro create an endless runner game, using executable code from a single line prompt.
Plot interactive economic data
Watch Gemini 2.5 Pro use its reasoning capabilities to create an interactive bubble chart to visualize economic and health indicators over time.
Animate complex behavior
See how Gemini 2.5 Pro creates an interactive Javascript animation of colorful boids inside a spinning hexagon.
Code particle simulations
Watch Gemini 2.5 Pro use its reasoning capabilities to create an interactive simulation of a reflection nebula.
Performance
Gemini 2.5 Pro leads common benchmarks by meaningful margins.
| Benchmark | Notes | Gemini 2.5 Pro Thinking | OpenAI o3 High | OpenAI o4-mini High | Claude Opus 4 32k thinking | Grok 3 Beta Extended thinking | DeepSeek R1 05-28 |
|---|---|---|---|---|---|---|---|
| Input price | $/1M tokens (no caching) | $1.25 $2.50 > 200k tokens | $10.00 | $1.10 | $15.00 | $3.00 | $0.55 |
| Output price | $/1M tokens | $10.00 $15.00 > 200k tokens | $40.00 | $4.40 | $75.00 | $15.00 | $2.19 |
| Reasoning & knowledge Humanity's Last Exam (no tools) | 21.6% | 20.3% | 14.3% | 10.7% | — | 14.0%* | |
| Science GPQA diamond | single attempt | 86.4% | 83.3% | 81.4% | 79.6% | 80.2% | 81.0% |
| multiple attempts | — | — | — | 83.3% | 84.6% | — | |
| Mathematics AIME 2025 | single attempt | 88.0% | 88.9% | 92.7% | 75.5% | 77.3% | 87.5% |
| multiple attempts | — | — | — | 90.0% | 93.3% | — | |
| Code generation LiveCodeBench (UI: 1/1/2025-5/1/2025) | single attempt | 69.0% | 72.0% | 75.8% | 51.1% | — | 70.5% |
| Code editing Aider Polyglot | 82.2% diff-fenced | 79.6% diff | 72.0% diff | 72.0% diff | 53.3% diff | 71.6% | |
| Agentic coding SWE-bench Verified | single attempt | 59.6% | 69.1% | 68.1% | 72.5% | — | — |
| multiple attempts | 67.2% | — | — | 79.4% | — | 57.6% | |
| Factuality SimpleQA | 54.0% | 48.6% | 19.3% | — | 43.6% | 27.8% | |
| Factuality FACTS grounding | 87.8% | 69.6% | 62.1% | 77.7% | 74.8% | — | |
| Visual reasoning MMMU | single attempt | 82.0% | 82.9% | 81.6% | 76.5% | 76.0% | no MM support |
| multiple attempts | — | — | — | — | 78.0% | no MM support | |
| Image understanding Vibe-Eval (Reka) | 67.2% | — | — | — | — | no MM support | |
| Video understanding VideoMMMU | 83.6% | — | — | — | — | no MM support | |
| Long context MRCR v2 (8-needle) | 128k (average) | 58.0% | 57.1% | 36.3% | — | 34.0% | — |
| 1M (pointwise) | 16.4% | no support | no support | no support | no support | no support | |
| Multilingual performance Global MMLU (Lite) | 89.2% | — | — | — | — | — |
Methodology
Gemini results: All Gemini scores are pass @1."Single attempt" settings allow no majority voting or parallel test-time compute; "multiple attempts" settings allow test-time selection of the candidate answer. They are all run with the AI Studio API for the model-id gemini-2.5-pro-preview-06-05 with default sampling settings. To reduce variance, we average over multiple trials for smaller benchmarks. Aider Polyglot score is the pass rate average of 3 trials. Vibe-Eval results are reported using Gemini as a judge.
Non-Gemini results: All the results for non-Gemini models are sourced from providers' self reported numbers unless mentioned otherwise below.
All SWE-bench Verified numbers follow official provider reports, using different scaffoldings and infrastructure. Google's scaffolding for "multiple attempts" for SWE-Bench includes drawing multiple trajectories and re-scoring them using model's own judgement.
Thinking vs not-thinking: For Claude 4 results are reported for the reasoning model where available (HLE, LCB, Aider). For Grok-3 all results come with extended reasoning except for SimpleQA (based on xAI reports) and Aider. For OpenAI models high level of reasoning is shown where results are available (except for GPQA, AIME 2025, SWE-Bench, FACTS, MMMU).
Single attempt vs multiple attempts: When two numbers are reported for the same eval higher number uses majority voting with n=64 for Grok models and internal scoring with parallel test time compute for Anthropic models.
Result sources: Where provider numbers are not available we report numbers from leaderboards reporting results on these benchmarks: Humanity's Last Exam results are sourced from https://agi.safe.ai/ and https://scale.com/leaderboard/humanitys_last_exam, AIME 2025 numbers are sourced from https://matharena.ai/. LiveCodeBench results are from https://livecodebench.github.io/leaderboard.html (1/1/2025 - 5/1/2025 in the UI), Aider Polyglot numbers come from https://aider.chat/docs/leaderboards/. FACTS come from https://www.kaggle.com/benchmarks/google/facts-grounding. For MRCR v2 which is not publicly available yet we include 128k results as a cumulative score to ensure they can be comparable with other models and a pointwise value for 1M context window to show the capability of the model at full length. The methodology has changed in this table vs previously published results for MRCR v2 as we have decided to focus on a harder, 8-needle version of the benchmark going forward.
API costs are sourced from providers' website and are current as of June 5th.
* indicates evaluated on text problems only (without images)
Input and output price reflects text, image and video modalities.
Model information
- Name
- 2.5 Pro
- Status
- General availability
- Input
-
- Text
- Image
- Video
- Audio
- Output
-
- Text
- Input tokens
- 1M
- Output tokens
- 64k
- Knowledge cutoff
- January 2025
- Tool use
-
- Function calling
- Structured output
- Search as a tool
- Code execution
- Best for
-
- Reasoning
- Coding
- Complex prompts
- Availability
-
- Gemini app
- Google AI Studio
- Gemini API
- Vertex AI
- Documentation
- View developer docs
- Model card
- View model card
- Technical report
- View technical report