See [`docs/model-failover.md`](/concepts/model-failover) for how auth profiles rotate (OAuth vs API keys), cooldowns, and how that interacts with model fallbacks.
- [Claude Opus 4.5](https://www.anthropic.com/claude/opus): default primary for assistant + general work. It’s pricey and cap-prone, so consider the [Claude Max $200 subscription](https://www.anthropic.com/pricing/) if you live here.
- [Claude Sonnet 4.5](https://www.anthropic.com/claude/sonnet): default fallback when Opus caps out. Similar behavior with fewer limit headaches.
- [GPT-5.2-Codex](https://developers.openai.com/codex/models): recommended for coding and sub-agents. Prefer the [Codex CLI](https://developers.openai.com/codex/cli) if you want the strongest feel.
Suggested stacks:
- Assistant-first: Opus 4.5 primary → Sonnet 4.5 fallback.
- Agentic coding: Opus 4.5 primary → GPT-5.2-Codex for sub-agents → Sonnet 4.5 fallback.
- [Claude Opus 4.5](https://www.anthropic.com/claude/opus): best overall quality in Clawdbot, especially for “assistant” work. Tradeoff is cost and hitting usage limits quickly.
- [Claude Sonnet 4.5](https://www.anthropic.com/claude/sonnet): common fallback when Opus caps out. Similar behavior with fewer limit headaches.
- [Gemini 3 Pro](https://deepmind.google/en/models/gemini/pro/): some users felt it maps well to Clawdbot’s structure. Vibe was “fits the framework” more than “best at everything.”
- [GLM](https://www.zhipuai.cn/en/): used successfully as a worker model under orchestration. Seen as strong for delegated/secondary tasks, not the primary brain.
- [MiniMax M2.1](https://platform.minimax.io/docs/guides/models-intro): “good enough” for grunt work or a cheap fallback. Community nickname was “Temu-Sonnet,” i.e. usable but not Sonnet-level polish.
- [Antigravity](https://blog.google/technology/ai/google-ai-updates-november-2025/) (Claude Opus access): some reported extra Opus quota. Pricing/limits were unclear, so the value is hard to predict.
- [GPT-5.2-Codex](https://developers.openai.com/codex/models) inside Clawdbot: reported as rough for conversation/assistant tasks when embedded. Same notes said Codex felt stronger via the [Codex CLI](https://developers.openai.com/codex/cli) than embedded use.
- [Grok](https://docs.x.ai/docs/models/grok-4): people tried it and then abandoned it. No strong upside showed up in the notes.
- Token burn feels higher than expected in long sessions; people suspect context buildup + tool outputs. Pruning/compaction helps. Check session logs before blaming providers. See [/concepts/session](/concepts/session) and [/concepts/model-failover](/concepts/model-failover).
Want a tailored stack? Share whether you’re using Clawdbot or Clawdis and your main workload (agentic coding vs “assistant” work), and we can suggest a primary + fallback set based on these reports.