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Balance accuracy, speed, and cost by picking the right model and reasoning level for each task. Every model we offer meets proprietary quality and cost-efficiency requirements. Model quality evolves quickly, and we tune the CLI defaults as the ecosystem shifts. Use this guide as a snapshot of how the major options compare today, and expect to revisit it as we publish updates. This guide was last updated on Wednesday, June 3rd 2026.

1 · Current stack rank (June 2026)

* Anthropic requires all Mythos-class models comply with 30 day data retention for trust and safety, please see more information here. As of June 12, 2026, Claude Fable 5 is not currently available—see Anthropic’s update on Mythos access here.
We ship model updates regularly. When a new release overtakes the list above, we update this page and the CLI defaults.

2 · Match the model to the job

Claude Opus 4.8 is the newest top-tier option for extremely complex architecture decisions or critical work where you need maximum reasoning capability. Claude Opus 4.7 and Claude Opus 4.6 remain excellent alternatives, and Opus 4.6 Fast is tuned for faster responses at a higher cost. Most tasks don’t require Opus-level power—start with Sonnet 4.6 or Sonnet 4.5 and escalate only if needed.
Tip: you can swap models mid-session with /model or by toggling in the settings panel (Shift+TabSettings).

3 · Switching models mid-session

  • Use /model (or Shift+Tab → Settings → Model) to swap without losing your chat history.
  • If you change providers (e.g. Anthropic to OpenAI), the CLI converts the session transcript between Anthropic and OpenAI formats. The translation is lossy—provider-specific metadata is dropped—but we have not seen accuracy regressions in practice.
  • For the best context continuity, switch models at natural milestones: after a commit, once a PR lands, or when you abandon a failed approach and reset the plan.
  • If you flip back and forth rapidly, expect the assistant to spend a turn re-grounding itself; consider summarizing recent progress when you switch.

4 · Reasoning effort settings

  • Opus 4.8: Off / Low / Medium / High / Max (default: High)
  • Opus 4.7: Off / Low / Medium / High / Max (default: High)
  • Opus 4.6 / Opus 4.6 Fast: Off / Low / Medium / High / Max (default: High)
  • Sonnet 4.6: Off / Low / Medium / High / Max (default: High)
  • Opus 4.5 / Sonnet 4.5 / Haiku 4.5: Off / Low / Medium / High (default: Off)
  • GPT-5.6 Sol / Terra / Luna: None / Low / Medium / High / Extra High / Max (default: Medium)
  • GPT-5.4: None / Low / Medium / High / Extra High (default: Medium)
  • GPT-5.2: Off / Low / Medium / High / Extra High (default: Low)
  • GPT-5.2-Codex: None / Low / Medium / High / Extra High (default: Medium)
  • GPT-5.3-Codex: None / Low / Medium / High / Extra High (default: Medium)
  • Gemini 3.1 Pro: Low / Medium / High (default: High)
  • Gemini 3 Flash: Minimal / Low / Medium / High (default: High)
  • Grok 4.5: Low / Medium / High (default: Medium)
  • Droid Core (GLM-5): None only (default: None; no image support)
  • Droid Core (GLM-5.1): None only (default: None; no image support)
  • Droid Core (Kimi K2.6): Off / High (default: High)
  • Droid Core (MiniMax M2.7): Low / Medium / High (default: High)
Reasoning effort increases latency and cost—start low for simple work and escalate as needed. Max is available on the GPT-5.6 family (Sol, Terra, Luna), Claude Opus 4.8, Claude Opus 4.7, the Opus 4.6 family (Opus 4.6 and Opus 4.6 Fast), and Sonnet 4.6. Extra High is available on the GPT-5.6 family (Sol, Terra, Luna), GPT-5.4, GPT-5.2, GPT-5.2-Codex, and GPT-5.3-Codex.
Change reasoning effort from /modelReasoning effort, or via the settings menu.

5 · Bring Your Own Keys (BYOK)

Factory ships with managed Anthropic and OpenAI access. If you prefer to run against your own accounts, BYOK is opt-in—see Bring Your Own Keys for setup steps, supported providers, and billing notes.

Open-source models

Droid Core (GLM-5), Droid Core (GLM-5.1), Droid Core (Kimi K2.6), and Droid Core (MiniMax M2.7) are open-source alternatives available in the CLI. They’re useful for:
  • Air-gapped environments where external API calls aren’t allowed
  • Cost-sensitive projects needing unlimited local inference
  • Privacy requirements where code cannot leave your infrastructure
  • Experimentation with open-source model capabilities
Note: GLM-5 and GLM-5.1 do not support image attachments. Kimi K2.6 and MiniMax M2.7 do support images. Kimi K2.6 adds an Off/High reasoning toggle, while MiniMax M2.7 (the cheapest model available, with 0.12× multiplier) supports Low/Medium/High reasoning. For image-based workflows, use Claude, GPT, Kimi, or MiniMax M2.7. To use open-source models, you’ll need to configure them via BYOK with a local inference server (like Ollama) or a hosted provider. See BYOK documentation for setup instructions.

6 · Keep notes on what works

  • Track high-impact workflows (e.g., spec generation vs. quick edits) and which combinations of model + reasoning effort feel best.
  • Ping the community or your Factory contact when you notice a model regression so we can benchmark and update this guidance quickly.