Llama 4 Maverick Pricing Breakdown
Llama 4 Maverick is Meta’s open-weight model, which means the model itself costs $0. The pricing data in our calculator shows $0/$0 per million tokens because there’s no per-token licensing fee. But “free” is doing a lot of heavy lifting in that sentence — you still need hardware to run it.
The Real Cost: Compute
Open-weight doesn’t mean free inference. Here’s what you’re actually paying for:
- Cloud GPUs — Llama 4 Maverick needs serious hardware. Expect 4-8 A100s or equivalent. At cloud rates, that’s $8-15/hour depending on your provider and region.
- Storage — the model weights need to be stored and loaded. Not a huge cost, but it’s there.
- Engineering time — setting up inference servers, handling scaling, managing uptime. This is the hidden cost most people underestimate.
When Open-Weight Makes Sense
The math works out in your favor when:
- High, consistent volume — if you’re pushing enough traffic to keep GPUs busy 70%+ of the time, your effective per-token cost drops below most API providers
- Data privacy requirements — no data leaves your infrastructure, which some industries require
- Customization — you want to fine-tune, quantize, or modify the model in ways commercial APIs don’t allow
- Predictable billing — fixed hardware costs instead of variable per-token charges
When It Doesn’t
Self-hosting is a losing bet when:
- Your traffic is bursty or low-volume (idle GPUs are expensive GPUs)
- You don’t have ML ops expertise on the team
- You need to move fast and can’t spend weeks on infrastructure
For most startups and smaller teams, hosted Llama 4 endpoints from providers like Together AI or Fireworks are the sweet spot. You get the cost benefits of an open model without the infrastructure headache, typically at $0.20-1.00 per million tokens.
Use the calculator above to compare what you’d pay across all models — and remember that Llama 4’s “$0” in the table represents the model cost only, not your total spend.