Gemini 3 Pro vs Gemini 1.0 Pro
Compare pricing, context windows, and strengths for Gemini 3 Pro by Google and Gemini 1.0 Pro 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 1.0 Pro
A versatile multimodal model optimized for balanced performance across reasoning, language, and code tasks.
View Gemini 1.0 ProGemini 3 Pro vs Gemini 1.0 Pro at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | Gemini 3 Pro | Gemini 1.0 Pro |
|---|---|---|
| Provider | ||
| Model type | Text | Text |
| Context window | 1M tokens | 128K tokens |
| Input price | $4 / 1M tokens | $0.5 / 1M tokens |
| Output price | $18 / 1M tokens | $1.5 / 1M tokens |
| Status | Superseded by Gemini 3.1 Pro | Current |
How Gemini 3 Pro and Gemini 1.0 Pro differ
What the numbers mean in practice when choosing between Gemini 3 Pro and Gemini 1.0 Pro.
-
Gemini 1.0 Pro is 88% cheaper on input tokens ($0.5 vs $4 per million), which adds up quickly in document-heavy workloads.
-
Gemini 1.0 Pro is 92% cheaper on output tokens ($1.5 vs $18 per million) - the bigger factor for tools that generate long documents.
-
Gemini 3 Pro's 1M tokens context window is roughly 7.8x larger than Gemini 1.0 Pro's 128K tokens, so it can work across bigger codebases, contracts, or archives in one pass.
-
Gemini 3 Pro has been superseded by Gemini 3.1 Pro - for new builds, consider the newer model first.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 1.0 Pro
1. Strong all-purpose performance
- Designed as Google's balanced middle-tier model.
- Handles a wide range of tasks: reasoning, writing, coding, and problem-solving.
2. Natively multimodal understanding
- Trained from the ground up on text, images, audio, and video.
- More consistent multimodal reasoning than stitched-together architectures.
3. Great cost-to-capability ratio
- Offers much of Gemini Ultra's reasoning quality at a fraction of the cost.
- Strong default choice for large-scale production workloads.
4. Reliable reasoning and factual performance
- Performs well on benchmarks like MMLU, MMMU, and code reasoning.
- Handles long-form analysis, multi-step reasoning, and structured problem solving.
5. Advanced coding capabilities
- Supports major languages such as Python, Java, C++, Go.
- Generates, edits, debugs, and explains code with high accuracy.
- Powers advanced coding systems like AlphaCode 2.
6. Efficient and scalable
- Optimized for Google TPUs for lower latency and faster inference.
- Suitable for batch workloads, agents, and complex multi-step pipelines.
7. Strong multimodal reasoning
- Understands math, physics, and scientific diagrams.
- Handles mixed data inputs (charts + text, screenshots + instructions, etc.).
8. Enterprise-ready reliability
- Available through Google AI Studio and Vertex AI.
- Benefits from enterprise-grade governance, safety, privacy, and compliance.
Use Gemini 3 Pro or Gemini 1.0 Pro - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by Gemini 3 Pro or Gemini 1.0 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 3 Pro or Gemini 1.0 Pro. No code, no API keys, no deployment.
Switch models without rebuilding
Start on Gemini 3 Pro, test the same tool on Gemini 1.0 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 3 Pro or Gemini 1.0 Pro - connected to the tools you already use.
Related comparisons
See how Gemini 3 Pro and Gemini 1.0 Pro stack up against other models in the directory.
FAQs
Gemini 1.0 Pro is generally cheaper: $0.5 input / $1.5 output per million tokens, versus $4 / $18 for Gemini 3 Pro. Actual cost depends on how many tokens your workload reads and writes.
Gemini 3 Pro has the larger context window at 1M tokens, compared to 128K tokens for Gemini 1.0 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 1.0 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 3 Pro, Gemini 1.0 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 3 Pro or Gemini 1.0 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.