BaseRT vs Cleanlist AI: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of BaseRT and Cleanlist AI — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

BaseRT

Base Compute

Free

BaseRT is a high-performance LLM runtime for Apple Silicon that runs open-source models locally, faster than llama.cpp and MLX.

Apple Silicon Optimized Runtime: A native inference engine tuned for M-series chips that outperforms llama.cpp and MLX on decode and prefill benchmarks.
One-Line Install: BaseRT ships as a single curl-piped install script, so users can go from download to serving a model in seconds.
Broad Open-Source Model Support: Runs Qwen3, Llama 3.1/3.2, Gemma 3/4, Mistral, Phi-3, and Nomic BERT out of the box, with quantized (Q4/Q8) weights.
Local Serving for Coding Agents: `basert serve <model>` exposes a local endpoint that pairs with the pi plugin so coding agents run fully on-device with no API keys.
Privacy by Default: All inference happens on the user's machine, so prompts, code, and outputs never leave the device.
Benchmark-Driven Performance: Publishes tokens/sec comparisons on Apple M5 Pro against MLX and llama.cpp for reproducibility.

On-Device Coding Assistant: Engineers pair BaseRT with a local coding agent to get autocomplete and refactoring without sending source code to a cloud API.
Private Model Evaluation: ML practitioners benchmark open-source models on their own laptop without renting GPUs or exposing test data.
Offline LLM Applications: Developers ship desktop apps that call a locally served model, avoiding rate limits and per-token costs.
Prototyping on Apple Silicon: Researchers experiment with new quantizations and open-weight models on M-series Macs at high throughput.
Enterprise On-Prem Inference: Teams with data-residency constraints run production inference on employee devices instead of external APIs.

Cleanlist

Freemium

AI-powered B2B prospecting and enrichment that turns plain-English prompts into verified, CRM-ready lead lists via a 15-provider waterfall.

Conversational List Builder: Describe any target list in plain English and the Co-Pilot returns a fully enriched, CRM-ready set of leads.
15-Provider Waterfall Enrichment: Providers compete in real time on every contact to deliver 98% email accuracy and 85% direct-dial find rates.
Company-First ICP Search: Filter by industry, size, geography, tech stack, hiring signals, and funding stage, then pull every relevant decision-maker.
LinkedIn & Sales Navigator Extension: Open any profile, click Cleanlist, and get a verified email and direct dial in two seconds.
CSV Enrichment: Drop 500 rows and each is run through the full waterfall, returning verified emails, direct dials, titles, and firmographics.
Native CRM Sync: One-click, two-way sync to HubSpot, Salesforce, Pipedrive, Outreach, Salesloft, and lemlist — no Zapier required.
AI Columns and Smart Agents: AI-generated columns add ICP scoring, company summaries, and competitor notes with the reasoning behind each answer.

Outbound Prospecting: Sales reps build targeted lead lists on demand and push them straight to a sequencer.
RevOps CRM Cleanup: Ops teams re-enrich stale HubSpot or Salesforce records to restore email deliverability and phone connect rates.
Inbound Speed-to-Lead: Trigger enrichment on new form fills so reps have full context within minutes of a signup.
ABM Account Expansion: Discover every relevant decision-maker inside a target account list without juggling multiple databases.
Sales Stack Consolidation: Replace ZoomInfo/Apollo plus a separate email verifier and phone tool with one credit-based platform.