Damnit AI LLC · local execution engine
Cloud throughput. Your hardware.
Damnit is a native C++ execution engine that runs memory-bound inference on the machines a customer already owns. The work stays in the building, the bill stops scaling with tokens, and the arithmetic is checked before a result is reported.
Measured 10 November 2026 · 11th Gen Intel(R) Core(TM) i3-1115G4 @ 3.00GHz · public challenge CLI. Every figure links to a record with the machine, load, binary hash and checksum. Evidence →
The cloud bill is a routing decision.
Work that fits on one machine does not need to be rented by the hour. Damnit moves the computation back to hardware the customer already owns.
No marginal compute
No per-token invoice, no egress, no idle cluster. Capacity is the machine already on the desk.
Data stays put
Inputs are processed where they already live. Nothing is uploaded to a third party in order to be computed on.
Same answer every time
Fixed memory, deterministic execution, and a checksum gate that fails the run rather than report a wrong result.
One engine. Three properties.
Damnit is sold as an engine, not a framework. It is licensed, verified at startup, and measured against the same workload it runs.
Bounded memory
The working set stays inside a fixed budget instead of growing with context or batch size.
Allocation-free steady state
Aligned arenas are reserved once; the hot path does not ask the heap for memory.
Fails closed
If the arithmetic does not agree, the run exits non-zero. A wrong number is never the cheap outcome.
Proof, not adjectives.
A benchmark is worth the record behind it. Ours carries the machine, the load around the run, the exact binary and a checksum that had to match.
- 01
A published record.9.84 GB/s on one thread, 19.85 GB/s across 4, checksum 1945. The JSON is public.
- 02
A gate that can fail.Exit 0,
RESULT: PASS, an invariant of MATCH, and three checksums that must agree. A miss is not published. - 03
A CLI you can run.The challenge binary is public, carries no model code, and reports your hardware rather than ours.
On the real 3.66 GiB packed file, the licensed kernel measures 0.04 ns per weight against 3.09 ns for the scalar reference — 82× — and reads it at 4.23 GB/s warm on 4 threads, with checksum 8,730,749 matching. The kernel record →
The record, the gate and the software checks → · Run the challenge yourself →
Licensed, not shipped.
The engine is leased as a subscription. Checkout issues a signed licence key; the binary verifies it at startup and enforces the seat count. When the subscription ends, the engine stops at its next check.
- Individual — $19 / month. One machine, one developer, cancel any time.
- Commercial — two machines. Arranged directly: aaron@damnit-ai.com.
- Already leasing? Manage or cancel in the billing portal.
The verification check is online. A machine that cannot reach the licence server is refused, by design.
Quantization models: private
Kernel binary: licensed download
Runtime: verified at startup
You licence the engine, not the recipe. Source and model evaluation is available under a mutual NDA; nothing about how the engine is built is published.