Tests and benchmarksEvery result read again at benchmarks.eigna.ai on 24 October 2026

We publish our results. Including the ones we lose.

At the gate so far
3 held, 0 released
Proof Ladder
1 of 54 cells done
Published
Benchmark 001, 14 October 2026

The lead story · Benchmark 001

17.8%

Our first training run cut forecast error 17.8% against its base model. It is not yet ahead of a simple last value baseline, and we publish that too.

Base model, Kronos-small1.750%
Our first training run1.439%
Last value baselineStill ahead of ours1.392%
Benchmark 001. Forecast error (CRPS), lower is better. 243 held-out days, hourly BTC and ETH, 24 hours ahead. Run on 14 October 2026.
  • 0 of 3Simple baselines beatenLast value, EWMA, GARCH(1,1)
  • 57.3%Band coverageTarget 80%
  • +4.4%Paper tradingBase model +15.0%

Case 001

Held at the gate.

Three candidates of our first client’s forecasting model met the gate in October 2026. All three were held. Release 1 was not issued, and nothing untested reached the desk.

Eigna TLM, Case 001
Release record
  • Candidate 3

    23 October, shrinkage head

    Held
  • Candidate 2

    14 October, calibrated

    Held
  • Candidate 1

    14 October, LoRA, 4 runs

    Held
  • Release 1

    Not issued

    No release

The Proof Ladder

1 of 54 cells done.

Six rungs, nine model families. We publish the empty cells too: they are what we still have to prove.

Proof Ladder cells by family and rung
TLM, time seriesDonePartialTo runTo runTo runTo run
LLM, languageTo runTo runTo runTo runTo runTo run
VoiceTo runTo runTo runTo runTo runTo run
ImageTo runTo runTo runTo runTo runTo run
VideoTo runTo runTo runTo runTo runTo run
RoboticsTo runTo runTo runTo runTo runTo run
Typed routerTo runTo runTo runTo runTo runTo run
3DTo runTo runTo runTo runTo runTo run
GuardrailsTo runTo runTo runTo runTo runTo run
Done 1 Partial 1 To run 52
Read on 24 October 2026 at benchmarks.eigna.ai.

How we claim

A metric, a baseline and a date. Never adjectives.

  1. 01Name the metricIn plain words, with its unit, and whether lower or higher is better.
  2. 02Name the baselineThe simplest one first. Beating the base model is not enough.
  3. 03Date itThe day of the run and the day we read it again.
  4. 04Publish itWhether it wins or loses, next to the win, at the same size.
Runs today: the first expert, the scoring harness and sealed tests, training on local machines and H200 GPUs, benchmarks.eigna.ai.

Test Lab

Your proof, on your work.

In about four weeks, on your own data in a sealed setup, we show whether an Eigna expert beats your baseline. If it does not, you keep the report.