GPT-4o mini vs Claude 4.8 Opus

1. Fast, cost-efficient performance

• Designed for low-latency, high-throughput workloads.
• Ideal for production systems where speed and budget matter more than deep reasoning power.

2. Great for focused NLP tasks

• Excels at classification, tagging, entity extraction, rewriting, paraphrasing, and SEO tasks.
• Strong at translation and keyword generation due to efficient language understanding.

3. Multimodal input capable (text + image)

• Accepts images for lightweight visual analysis, categorization, or extraction.
• Outputs text only, ensuring deterministic and easily integrated responses.

4. Supports advanced developer features

• Structured Outputs for predictable schemas.
• Function calling for building tool-augmented agents.
• Fully compatible with Batch API for large-scale processing.

5. Easy to fine-tune

• One of the best OpenAI models for domain-specific fine-tuning.
• Allows organizations to compress larger models' behavior (like GPT-4o) into a smaller footprint.

6. Suitable for distillation workflows

• Can approximate GPT-4o or GPT-5 outputs using distillation, dramatically reducing cost.
• Enables scalable deployment for high-volume applications.

7. Large context window for its size

• 128K context supports multi-step tasks, multi-document inputs, and long-running conversations.
• Useful for agents that need memory across extended sessions.

8. Reliable for commercial production

• Stable, predictable, and low-variance outputs make it ideal for automation and enterprise stacks.
• Works well in synchronous or asynchronous pipelines.

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.