Gemini 3 Pro vs Gemini 2.5 Pro Experimental
Compare pricing, context windows, and strengths for Gemini 3 Pro by Google and Gemini 2.5 Pro Experimental by Google - and see how to put either to work in Appaca.
Gemini 3 Pro
Google's most intelligent multimodal model designed for advanced reasoning, coding, and agentic tasks.
View Gemini 3 ProGemini 2.5 Pro Experimental
Google's most advanced thinking model, leading benchmarks in reasoning, science, math, and coding with a massive multimodal context window.
View Gemini 2.5 Pro ExperimentalGemini 3 Pro vs Gemini 2.5 Pro Experimental at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | Gemini 3 Pro | Gemini 2.5 Pro Experimental |
|---|---|---|
| Provider | ||
| Model type | Text | Text |
| Context window | 1M tokens | 1.05M tokens |
| Input price | $4 / 1M tokens | $1.5 / 1M tokens |
| Output price | $18 / 1M tokens | $6 / 1M tokens |
| Status | Superseded by Gemini 3.1 Pro | Current |
How Gemini 3 Pro and Gemini 2.5 Pro Experimental differ
What the numbers mean in practice when choosing between Gemini 3 Pro and Gemini 2.5 Pro Experimental.
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Gemini 2.5 Pro Experimental is 63% cheaper on input tokens ($1.5 vs $4 per million), which adds up quickly in document-heavy workloads.
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Gemini 2.5 Pro Experimental is 67% cheaper on output tokens ($6 vs $18 per million) - the bigger factor for tools that generate long documents.
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Context windows are close: Gemini 3 Pro handles 1M tokens and Gemini 2.5 Pro Experimental handles 1.05M tokens.
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Gemini 3 Pro has been superseded by Gemini 3.1 Pro - for new builds, consider the newer model first.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
Gemini 3 Pro
1. State-of-the-art reasoning
- Top performance across academic reasoning, scientific knowledge, math, and complex problem-solving.
- Excels at long-horizon, multi-step workflows and deep logical interpretation.
2. World-leading multimodal capabilities
- Natively understands text, images, videos, audio, and code.
- Ranked highest on benchmarks like MMMU-Pro, Video-MMMU, ScreenSpot-Pro.
3. Exceptional coding + agentic workflows
- Strong in competitive coding and real-world agentic tasks (SWE-Bench Verified, Terminal-Bench, LiveCodeBench).
- Improved tool calling, planning, and execution for autonomous or semi-autonomous agents.
4. Powerful for long-context tasks
- Effective at 128K-1M context windows with high retrieval accuracy.
- Ideal for document-heavy workflows, research, analysis, multi-file coding, and multi-document reasoning.
5. Strong information synthesis and interpretation
- Outperforms peers in chart reasoning, OCR, structured extraction, and screen understanding.
- Excellent at combining multimodal inputs into coherent, concise answers.
6. High reliability for enterprise tasks
- Benchmarks show superior factuality, grounding, and parametric knowledge.
- Strong multilingual accuracy and global commonsense performance.
7. Optimized for production agents
- Designed for complex multi-step planning, simultaneous task execution, and improved consistency.
- Works across coding, research, creative workflows, UI generation, and data-heavy applications.
Gemini 2.5 Pro Experimental
1. State-of-the-art reasoning performance
- #1 on LMArena human preference leaderboard.
- Excels at advanced reasoning benchmarks like GPQA and AIME 2025.
- Achieves 18.8% on Humanity's Last Exam (no tools), representing frontier human-level reasoning.
2. New “thinking model” architecture
- Built with explicit reasoning steps internally before responding.
- Handles complex, multi-stage logic with higher accuracy and fewer hallucinations.
3. Elite science and mathematics capabilities
- Leads in math and science tasks across industry benchmarks.
- High performance without costly inference tricks like majority voting.
4. Exceptional coding abilities
- Major leap over Gemini 2.0 in coding performance.
- 63.8% on SWE-Bench Verified with custom agent setup.
- Strong at code transformation, debugging, and building agentic apps.
- Capable of generating full applications (e.g., a playable video game) from a single-line prompt.
5. Massive multimodal context
- Ships with a 1,000,000 token window (2M coming soon).
- Handles entire documents, datasets, video sequences, audio files, and large codebases.
- Maintains strong performance even at extreme context lengths.
6. Native multimodality across all inputs
- Understands and reasons over text, images, audio, video, and code.
- Designed for real-world, multi-source problem-solving and agent workflows.
7. Consistent high-quality outputs
- Improved post-training results in more accurate, coherent, and stylistically strong responses.
- Higher reliability across complex workloads.
8. Early availability for developers
- Available today in Google AI Studio for experimentation.
- Coming soon to Vertex AI with higher rate limits and production-ready access.
Use Gemini 3 Pro or Gemini 2.5 Pro Experimental - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by Gemini 3 Pro or Gemini 2.5 Pro Experimental - connected to your real data and ready for your whole team. No code, no deployment.
Describe it, and it's built
Tell the Appaca agent the internal tool you need and it builds a working app powered by Gemini 3 Pro or Gemini 2.5 Pro Experimental. No code, no API keys, no deployment.
Switch models without rebuilding
Start on Gemini 3 Pro, test the same tool on Gemini 2.5 Pro Experimental, and keep whichever performs better - the rest of your app stays exactly as it is.
Automated for the whole team
Schedule tools to run on autopilot - daily digests, weekly reports, real-time triggers - and share them with your whole team from one workspace.
Describe it, and it's built
Tell the Appaca agent what your team needs and it builds a working app powered by Gemini 3 Pro or Gemini 2.5 Pro Experimental - connected to the tools you already use.







Related comparisons
See how Gemini 3 Pro and Gemini 2.5 Pro Experimental stack up against other models in the directory.
FAQs
Gemini 2.5 Pro Experimental is generally cheaper: $1.5 input / $6 output per million tokens, versus $4 / $18 for Gemini 3 Pro. Actual cost depends on how many tokens your workload reads and writes.
Gemini 2.5 Pro Experimental has the larger context window at 1.05M tokens, compared to 1M tokens for Gemini 3 Pro. A larger window means the model can consider more text at once - useful for long contracts, codebases, or months of records.
It depends on the job. Compare the pricing, context window, and strengths above against your workload - and remember the choice isn't permanent. In Appaca you can build a tool on Gemini 3 Pro, test the same tool on Gemini 2.5 Pro Experimental, and switch at any time without rebuilding anything.
Yes. Appaca is a no-code AI workspace: describe the internal tool your team needs and the Appaca agent builds it as a working app powered by Gemini 3 Pro, Gemini 2.5 Pro Experimental, or any other model in the directory - with a built-in database, team access, and integrations. No API keys to wire up and nothing to deploy.
Build AI tools with Gemini 3 Pro or Gemini 2.5 Pro Experimental
Describe the tool your team needs and get a working app powered by the model you choose - with a built-in database, team access, and integrations. No code, no deployment.