o1-pro vs Claude 4.8 Opus

1. Maximum-compute o-series model

• Uses significantly more compute per query compared to o1.
• Produces deeper, more reliable reasoning chains.
• Best suited for high-stakes tasks that need correctness over speed.

2. Trained with reinforcement learning for deliberate thinking

• Explicit "think-before-answer" architecture.
• Excels at complex reasoning requiring multi-step analysis.

3. Very strong at math, science, coding, and technical proofs

• Handles long derivations, algorithm design, and difficult logic problems.
• Produces structured and explainable reasoning trails.

4. Great for multi-turn reasoning workflows

• Responses API optimized: can think over multiple internal turns before responding.
• Ideal for agentic reasoning pipelines.

5. Large context window

• 200,000-token context for large documents, multi-file review, and long reasoning traces.

6. Multimodal input (text + image)

• Can analyze images for mathematical diagrams, charts, handwritten content, UI layouts, etc.
• Output is text only.

7. Consistency, reliability, and depth

• Designed for situations where accuracy matters more than latency or cost.
• Strong error-checking and self-correction abilities.

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.