Side-by-side
| Axis | Llama 3.3 70B | Mistral Small 22B |
|---|---|---|
| Setup time | ollama pull llama3.3:70b. ~40 GB download. Needs 48 GB unified memory or 24 GB VRAM minimum. | ollama pull mistral-small:22b. ~13 GB download. Runs on 24 GB. |
| Security model | Local inference. No data leaves the machine. | Same. |
| Model support | 70B params, 4-bit quantised. 84% pass rate on our agent suite. | 22B params, 4-bit quantised. 76% pass rate. Apache 2.0 license. |
| Cost | Mac Mini M4 Pro 48 GB (€1,899) at ~9 tok/s. Mac Studio M3 Ultra 192 GB at ~22 tok/s. | Mac Mini M4 24 GB (€899) at ~21 tok/s. The cheapest credible mid-tier setup. |
| Ecosystem | Llama family has the broadest tool integrations and fine-tuning ecosystem. | Mistral models are popular for production deployments due to Apache 2.0 license. |
| Best for | When you need maximum local capability and have the hardware budget. | The price-quality sweet spot. Most local-LLM agent deployments should sit here. |
Verdict
Mistral Small 22B Q4 on a 24 GB Mac Mini M4 is the price-performance sweet spot for local-LLM agents in mid-2026. Llama 3.3 70B Q4 on 48 GB hardware is the capability ceiling at small form factor. Qwen 2.5 Coder 7B is the specialised pick for code-heavy workloads — we run all three in different roles.
Notes
- Llama 3 license is non-commercial-restricted but permits broad use; Mistral Apache 2.0 is fully permissive.
- Qwen 2.5 Coder 7B specifically beats Llama 3.3 70B on coding tasks despite being 10× smaller — match the model to the workload.
- All three improve quarterly. Re-benchmark every 6 months at minimum.
Going deeper
For the full landscape report including hosting economics, security posture and regulatory context, see the 2026 landscape report. For the OpenClaw-specific history, see the complete OpenClaw timeline.
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