Example highlights:
- Model safety research and evaluation.
- Autonomous agent design and simulation.
- Tools for reproducible ML pipelines.
Mainstream Foundation Models (compact comparison)
Models listed are representative; scores are an internal, relative summary for quick comparison.
| Model | Strengths | Agent Mode | Score (0–10) | Notes |
|---|---|---|---|---|
| GPT‑5 | General reasoning, multimodal, broad API ecosystem | Strong | 9.5 | High-quality assistants and integrations; strong agent tooling. |
| Gemini‑3 | Multimodal comprehension, tool use, robust instruction following | Strong | 9.0 | Balanced performance across reasoning and creativity workloads. |
| Claude‑4 | Safety-focused, long-context dialogue, compositional prompting | Good | 8.8 | Often chosen for conservative/high-trust applications. |
| Grok‑4 | Fast conversational performance, chat-centric design | Partial | 8.2 | Optimized for real-time chat; agent feature set evolving. |
Agent‑First Workflows
Agent mode — tying models to tools, state, and orchestrated reasoning — is a primary way to build useful, autonomous assistants. Priorities for agent design include safe tool invocation, robust error handling, capability‑scoped permissions, and human‑in‑the‑loop checkpoints for high‑risk actions.