Gemini 2.5 Pro Experimental vs Gemini 1.5 Pro
Compare pricing, context windows, and strengths for Gemini 2.5 Pro Experimental by Google and Gemini 1.5 Pro by Google - and see how to put either to work in Appaca.
Gemini 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 1.5 Pro
A next-generation multimodal model with breakthrough long-context capability up to 1M tokens and strong reasoning across text, code, audio, video, and images.
View Gemini 1.5 ProGemini 2.5 Pro Experimental vs Gemini 1.5 Pro at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | Gemini 2.5 Pro Experimental | Gemini 1.5 Pro |
|---|---|---|
| Provider | ||
| Model type | Text | Text |
| Context window | 1.05M tokens | 1M tokens |
| Input price | $1.5 / 1M tokens | $3.5 / 1M tokens |
| Output price | $6 / 1M tokens | $7 / 1M tokens |
| Status | Current | Current |
How Gemini 2.5 Pro Experimental and Gemini 1.5 Pro differ
What the numbers mean in practice when choosing between Gemini 2.5 Pro Experimental and Gemini 1.5 Pro.
-
Gemini 2.5 Pro Experimental is 57% cheaper on input tokens ($1.5 vs $3.5 per million), which adds up quickly in document-heavy workloads.
-
Gemini 2.5 Pro Experimental is 14% cheaper on output tokens ($6 vs $7 per million) - the bigger factor for tools that generate long documents.
-
Context windows are close: Gemini 2.5 Pro Experimental handles 1.05M tokens and Gemini 1.5 Pro handles 1M tokens.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
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.
Gemini 1.5 Pro
1. Breakthrough long-context window up to 1,000,000 tokens
- Can process 1 hour of video, 11 hours of audio, 700k+ words, or 100k+ lines of code in a single prompt.
- Supports advanced retrieval, reasoning, summarization, and cross-document tasks.
- Achieves 99% retrieval accuracy on 1M-token Needle-In-A-Haystack tests.
2. Strong multimodal reasoning across video, audio, images, and text
- Can analyze long videos (e.g., full silent films), track events, infer causality, and identify small details.
- Handles large complex documents like manuals, transcripts, and books.
3. High-performance reasoning and problem solving
- Comparable to Gemini 1.0 Ultra across many benchmarks.
- Excels at code reasoning, multi-step explanations, and large-scale codebase analysis.
4. Advanced code understanding and generation
- Performs problem-solving on codebases exceeding 100,000 lines.
- Capable of cross-file reasoning, debugging guidance, API comprehension, and generating structured code improvements.
5. Efficient Mixture-of-Experts (MoE) architecture
- Activates only relevant expert pathways per input.
- Enables faster training, lower latency, and more efficient serving.
- Dramatically improves scalability and inference speed.
6. Exceptional in-context learning capabilities
- Learns new tasks directly from long prompts without fine-tuning.
- Demonstrated by learning to translate a low-resource language (Kalamang) from a grammar manual.
7. High-fidelity multimodal understanding
- Reads, analyzes, and reasons about long PDFs, code repositories, images, and videos together.
- Enables new classes of applications: legal analysis, scientific review, codebase audits, long-form content generation, etc.
8. Safety and reliability first
- Undergoes extensive ethics, safety testing, and red-teaming.
- Improved representational safety and reduced hallucinations compared to previous generations.
9. Available for developers and enterprises
- Accessible via AI Studio and Vertex AI.
- Supports future pricing tiers for expanded context windows.
- Designed for real enterprise-scale workloads.
10. Widely capable mid-size model
- Positioned between Gemini Pro and Gemini Ultra generations.
- Well-balanced: reasoning, multimodality, long-context, and speed.
Use Gemini 2.5 Pro Experimental or Gemini 1.5 Pro - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by Gemini 2.5 Pro Experimental or Gemini 1.5 Pro - 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 2.5 Pro Experimental or Gemini 1.5 Pro. No code, no API keys, no deployment.
Switch models without rebuilding
Start on Gemini 2.5 Pro Experimental, test the same tool on Gemini 1.5 Pro, 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 2.5 Pro Experimental or Gemini 1.5 Pro - connected to the tools you already use.







Related comparisons
See how Gemini 2.5 Pro Experimental and Gemini 1.5 Pro 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 $3.5 / $7 for Gemini 1.5 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 1.5 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 2.5 Pro Experimental, test the same tool on Gemini 1.5 Pro, 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 2.5 Pro Experimental, Gemini 1.5 Pro, 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 2.5 Pro Experimental or Gemini 1.5 Pro
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.