Gemini 1.5 Pro vs Claude 4.8 Opus

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. Modest but tangible gains across the board

• 69.2% on SWE-bench Pro (+4.9 points over Opus 4.7's 64.3%), 88.6% on SWE-bench Verified, and a 1,890 Elo on GDPval-AA - about 121 Elo ahead of GPT-5.5.
• Anthropic frames it as an incremental refinement of Opus 4.7 rather than a step-change release.

2. The most reliable agent model Anthropic has shipped

• The only model to complete every case end-to-end on Anthropic's internal Super-Agent benchmark, beating prior Opus models and GPT-5.5 at parity on cost.
• Leads CursorBench across every effort level with more efficient tool calling - fewer steps for the same intelligence.
• 84% on Online-Mind2Web and stronger OSWorld-Verified scores make it the strongest computer-use and browser-agent model Anthropic has tested.

3. New highs for professional and legal work

• Highest score ever recorded on Anthropic's Legal Agent Benchmark, and the first model to break 10% on its all-pass standard.
• Roughly a 4x improvement in honesty and calibrated uncertainty versus Opus 4.7 on Anthropic's evaluations.

4. Cheaper, faster controls

• Standard pricing holds at $5/M input and $25/M output, unchanged from Opus 4.7.
• Fast mode now runs at 2.5x speed for $10/M input and $50/M output - about a third of what fast mode cost on prior Opus releases.
• A new effort dial gives finer control over how hard the model works before answering.

5. Long-horizon agent workflows

• 1M token context window in beta and up to 128K output tokens.
• Introduces Dynamic Workflows (research preview) in Claude Code - Opus can write its own orchestration script and run up to 16 concurrent / 1,000 total subagents in a single session.