Three months ago we were paying $80/month across our team:
- 3× ChatGPT Plus seats = $60/mo
- 1× Claude Pro = $20/mo
- Total: $960/year
Most of that spend was for one specific job: drafting marketing copy. Variations of social posts, landing-page hooks, blog intros. Stuff a 3B-parameter local model handles fine — it's not legal reasoning, it's not 200K-context analysis, it's just text generation at the level a content marketer needs.
So we replaced it with LockStack.
The Switch
LockStack bundles Llama 3.2 3B Q8 quantization in a desktop binary. Install once, runs offline forever, no cloud calls, no per-seat pricing.
$147 one-time. Pays back in month 2.
When Local Wins
Local AI isn't always the right answer. We're honest about this on our site — there are real tradeoffs:
Cloud still wins for:
- Latest GPT-4-class reasoning
- Real-time API integration with 50+ services
- 200K-context document analysis
- Multi-modal vision tasks
Local wins for:
- Marketing copy where the prompt contains client info you can't legally send to OpenAI
- Drafts referencing NDA'd material
- Healthcare agencies, legal firms, finserv compliance, cybersec consultants — anywhere data isn't supposed to leave the machine
- Anywhere predictable cost > marginal quality gain
The Specs
For curious devs, what runs LockStack on your laptop:
- 8GB RAM minimum, 16GB comfortable
- 4-core CPU from 2018+ (Intel Skylake, AMD Zen 2, Apple M1+)
- 5GB disk for binary + model
- No GPU required (faster with one)
Generation speed: ~12 tokens/sec on a 2024 MacBook Air. Faster than most people read.
Why $147 Once, Not $9/mo
We're a bootstrapped Korean software company. We don't need recurring revenue to survive — we need customers who stick with the tool for years.
So we sell desktop software the old way: you pay once, you own the binary, it works offline forever. No expiration emails. No price hikes. No 'we're sunsetting your tier.'
If you're a marketing agency, regulated-industry team, or anyone tired of paying $20/mo per seat for AI subs that train on your content — try us:
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