Best Models to Run OpenClaw Locally for a Law Office

The short answer

If client data can go through an external API: Claude Sonnet 4.5 or Opus (Anthropic API) — best accuracy, easiest setup.

If data must never leave your network: Llama 3 70B or Llama 3.3 70B via Ollama — fully air-gapped, competitive quality.

Option 1 — Claude Sonnet 4.5 via API (recommended for most firms)

Claude Sonnet 4.5 is the sweet spot for legal document work: it handles long context windows well, follows complex instructions reliably, and costs roughly $3/$15 per million input/output tokens. For typical OpenClaw tasks — summarising deposition transcripts, drafting correspondence, reviewing contract clauses — Sonnet's accuracy is hard to beat at this price point.

Setup is a single environment variable:

ANTHROPIC_API_KEY=sk-ant-...

Then in your OpenClaw config, set model: claude-sonnet-4-5. Your data transits Anthropic's API but is not used for training under the standard API terms.

Option 2 — Claude Opus for high-stakes work

If the firm needs the strongest possible reasoning — complex multi-party contracts, privilege review, nuanced legal research — Claude Opus 4.7 is the step up. It runs about 5× more expensive than Sonnet, so reserve it for tasks where errors have real consequences. Most firms use Sonnet for routine tasks and Opus only for final review passes.

Option 3 — Llama 3 70B locally via Ollama (air-gapped)

For firms with strict data-sovereignty requirements — where client data must never transit a third-party server — running a local model is the only compliant option. Llama 3 70B (Meta) and Llama 3.3 70B are both strong performers on legal reasoning benchmarks and run on a single high-end workstation or small server with 48 GB+ VRAM.

Install Ollama, pull the model, and point OpenClaw at the local endpoint:

ollama pull llama3.3:70b
# In OpenClaw config:
provider: ollama
model: llama3.3:70b
base_url: http://localhost:11434

Throughput is slower than API calls, but for a small law office processing documents in batch, this is usually acceptable. Quality is noticeably below Claude Opus on very complex reasoning but solid for document drafting, summarisation, and extraction tasks.

What the r/openclaw community recommends

The consensus in the thread: start with Claude Sonnet via API to validate your OpenClaw workflows, then evaluate whether a local model is needed. Many firms discover that Anthropic's data handling terms are acceptable after review, and the API option is far simpler to maintain long-term.

One highly-upvoted comment noted that OpenClaw's real value in a law office is cross-app automation — not just model quality. Tasks like "email this deposition PDF to the calendar bot and schedule prep time" or "monitor this Google Sheet for new client intake forms and draft welcome emails" are where OpenClaw outperforms a simple chat interface regardless of which model is underneath.