Gemini 3 Pro vs Claude 4.7 Opus

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.

1. State-of-the-art software engineering

• A notable upgrade over Opus 4.6 on the hardest coding tasks, with users reporting they can hand off work that previously required close supervision.
• Early partners reported double-digit gains on real-world benchmarks — e.g., Cursor saw CursorBench jump from 58% to 70%, and Rakuten-SWE-Bench resolution tripled versus Opus 4.6.
• Handles complex, long-running tasks with rigor: plans carefully, catches its own logical faults, and verifies its outputs before reporting back.

2. Long-horizon agent reliability

• Full 1M token context window at standard pricing, with state-of-the-art long-context consistency.
• Far fewer tool errors, stronger recovery from tool failures, and better follow-through on multi-step workflows — designed for async work like CI/CD, automations, and managing multiple agents in parallel.
• Stronger file-system-based memory, retaining useful notes across long, multi-session runs.

3. Sharper instruction following and honesty

• Takes instructions literally and precisely — existing prompts may need re-tuning since earlier models were more lenient.
• More honest about its own limits: reports missing data instead of fabricating plausible-but-wrong answers, and resists dissonant-data traps that tripped up Opus 4.6.

4. Substantially improved vision and multimodal reasoning

• Accepts images up to 2,576 px on the long edge (~3.75 MP) — over 3x more than prior Claude models.
• Unlocks dense-screenshot computer use, complex diagram extraction, and pixel-perfect reference tasks.
• Stronger document reasoning for enterprise analysis (e.g., 21% fewer errors than Opus 4.6 on Databricks' OfficeQA Pro).

5. Top-tier professional knowledge work

• State-of-the-art on the Finance Agent evaluation and GDPval-AA, with tighter, more professional finance analyses, models, and presentations.
• Strong on legal work — e.g., 90.9% on BigLaw Bench at high effort, with better-calibrated reasoning on review tables and ambiguous edits.
• Noted by design-focused partners as the best model for building dashboards and data-rich interfaces.

6. Modern effort and budget controls

• Introduces a new xhigh effort level between high and max for finer control over reasoning vs. latency.
• Task budgets (public beta) let developers guide token spend across long runs.
• Recommended to start with high or xhigh effort for coding and agentic use cases.