Generative AI · Decision models

#1 of 184 on JevBench

H2O-Lightning-4B ranks #1 of 184 on the JevBench Composite score for open-weights systems

Decision models get a situation and typed questions and must return calibrated answers, scored on intelligence, calibration, speed and cost. A 4B model with open weights.

Composite score
72.5
latency incl. network, board estimate
0.21 s
per 1,000 decisions, board estimate
$0.021

Composite, latency and cost, side by side

CompositeCapability top 1010 · sorted by Composite · higher is better

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  1. Rank 1Composite 72.5Capability 75.0H2O-Lightning-4B v1.1latency 210 mscost $0.021
  2. Rank 2Composite 71.8Torchcast Decision 4B (v1.2)latency 270 mscost $0.020
  3. Rank 3Composite 71.8Capability 82.5basal-omni-1.0-ultralatency 350 mscost $0.045
  4. Rank 4Composite 71.7Capability 79.6decisio v0.8.0 on gemma-4-31B-itlatency 240 mscost $0.041
  5. Composite 71.5Capability 77.1Jev 1.13.0reference · closed API · not rankedlatency 240 mscost $0.032
  6. Rank 5Composite 71.4Capability 81.7Quyet-1.0-Largelatency 380 mscost $0.045
  7. Rank 6Composite 70.9decider-12b v2latency 260 mscost $0.026
  8. Rank 7Composite 70.4decider-12b v1, stock Gemma-4-12B-itlatency 260 mscost $0.026
  9. Rank 8Composite 69.9torchcast-decision-12blatency 220 mscost $0.028
  10. Rank 9Composite 69.6Torchcast Decision 4B (v1.1)latency 190 mscost $0.020
  11. Rank 10Composite 68.9Winnow-12B Q8latency 380 mscost $0.028

Hatched: the board's Jev reference, a closed API listed but not ranked. Composite ranks 184 open-weights systems; Capability, the board's headline score, ranks the 131 inside its cost and latency caps. Latency includes network: for self-hosted models the board estimates it as 2 × its measured GPU time + 150 ms. Cost is the board's estimate. Benchmark Heaven, board v1.7.46.

Predictive AI · Time-series forecasting

#5 of 32 on fev-bench

TimeH2O-v1-tiny ranks #5 of 32 on the fev-bench leaderboard, by win rate

Zero-shot forecasting on real time series across many domains and frequencies, scored by probabilistic accuracy against a seasonal-naive baseline. 5.8M parameters.

win rate
77.3%
skill score
45.5%
parameters
5.8M

Win rate · top 8 of 32

higher is better

  1. #1Timestral-209M90.8%
  2. #2t0-gamma89.6%
  3. #3TimesFM-384.4%
  4. #4Chronos-278.1%
  5. #5TimeH2O-v1-tiny77.3%
  6. #6t0-beta75.6%
  7. #7TiRex-274.5%
  8. #8Toto-2.0-2.5B73.7%

Default leaderboard view. By skill score TimeH2O-v1-tiny is #7 of 32; with the closed-API models included it is #8 of 35. TimeH2O-v1-tiny has a non-commercial licence.

Agentic AI · Social forecasting

#3 of 25 on Social Simulation Arena

h2oGPTe Super Agent ranks #3 of 25 on Social Simulation Arena's overall standings

Entrants forecast the next public release of poll, sentiment and attention series. Forecasts are locked before the answer exists and scored against the published number.

arena score
+23
questions answered
26
h2oGPTe Super Agent
#3
H2O.ai Marina
#4

Arena score · top 8 of 25

higher is better · 0 = copying the last release

  1. #1Vac-SentimentExpectations+66
  2. #2Apodex-FutureFlow+27
  3. #3h2oGPTe Super Agent+23
  4. #4H2O.ai Marina+12
  5. #5YuLan-OneSim+10
  6. #6Vac-PublicOpinion+6
  7. #7worldVac+5
  8. #8Persistence (baseline)0

Entrants answer different numbers of questions. On the Season 0 main board h2oGPTe Super Agent is #4 of 26 and H2O.ai Marina #6.

Agentic AI · Future prediction

25 FutureX medals, 8 of them first places

h2oGPTe Super Agent ranks #1 of 24 on FutureX's weekly board for 2026 Oct. Week 2

Agents predict real-world events before they resolve, with a new board every week, scored once the answers are known.

latest weekly board
#1 of 24
first places
8
weekly boards with a medal, of 43 entered
18

Overall score, weekly board · top 8 of 24

higher is better

#ModelFrameworkOrganizationScore
1sonnet-5.5 - v2H2O AI Super Agent v1.82h2o.ai52.16
2sonnet-5.5 - 3xH2O AI Super Agent v1.82h2o.ai46.60
3GLM 5.2arce #1Indiv. AI Researcher46.05
4grok-4.7+sonnet-5.5 - v4H2O AI Super Agent v1.82h2o.ai45.56
5sonnet-5-5H2O AI Super Agent v1.82h2o.ai45.49
6grok-4.7+sonnet-5.5 - v1H2O AI Super Agent v1.82h2o.ai45.49
7GLM 5.2arce #2Indiv. AI Researcher45.00
8blue-fishblue-fishGoogle DeepMind43.88

Best of 8 H2O submissions. The agent runs on third-party base LLMs; medals count every H2O entry.

Predictive AI · Tabular foundation models

#5 of 13 on TALENT · #7 of 39 on TabArena

TabH2O ranks #5 of 13 on TALENT and #7 of 39 on TabArena

Two public benchmark suites of tabular classification and regression datasets, comparing tabular foundation models, AutoML and tuned gradient boosting.

TALENT
#5 of 13
TabArena
#7 of 39

Try it now

Run TabH2O on your own table in the browser, then get an API key for the REST endpoint.

Open the playground

TALENT · average rank across datasets · top 8 of 13

lower is better

  1. #1TabICL v2 (fine-tuned)3.48
  2. #2EXAONE-Tabular3.85
  3. #3TabPFN v3.04.23
  4. #4TabICL v24.40
  5. #5TabH2O v1.15.28
  6. #6TabPFN v2.65.89
  7. #7TabPFN v2.56.23
  8. #8AutoGluon8.07

TabArena · average rank across datasets · top 8 of 39

lower is better

  1. #1TabFM ensemble (official results)1.76
  2. #2TabFM (official results)3.31
  3. #3EXAONE-Tabular4.96
  4. #4TabPFN v3.06.37
  5. #5TabICL v2 (fine-tuned)7.18
  6. #6TabPFN v2.67.51
  7. #7TabH2O v1.18.39
  8. #8TabICL v28.76