Gemini 1.5 Pro vs Claude 4.6 Sonnet

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.

1. Most capable Sonnet model yet

• Anthropic describes Sonnet 4.6 as its most capable Sonnet model.
• It is a full upgrade across coding, computer use, long-context reasoning, agent planning, knowledge work, and design.

2. Stronger coding and professional task performance at Sonnet pricing

• Pricing remains at $3/M input and $15/M output, matching Sonnet 4.5.
• Anthropic says early-access developers strongly preferred it to Sonnet 4.5, and often even to Opus 4.5 for practical work.

3. Long-context, agent-friendly reasoning

• Supports up to a 1M token context window in beta.
• Anthropic reports better consistency, fewer false claims of success, fewer hallucinations, and more reliable follow-through on multi-step tasks.

4. Modern API controls for adaptive work

• Supports adaptive thinking and the effort parameter for balancing speed, cost, and depth.
• Gains dynamic filtering for web search and web fetch, helping agent workflows keep only relevant information in context.