Best Decision Models That Run on a CPU
CPU-class decision models (encoders and small decoders, under about 1.5B parameters) run next to the data with no GPU. Models are ranked by their Full score on the Jev Decision Index, a third-party board of 37 benchmarks with private held-out sets, until scores from our own Metatext Decision Benchmark are published. Latency is the board's median per call on its GPU runner.
Ranked list (top 25)
| # | Model | Decision Index | ECE | p50 latency | Per 1k decisions | Params |
|---|---|---|---|---|---|---|
| 1 | OneJev1.5-0.8B OmniJevOpen weights | 29.0 | 0.035 | 83 ms | — | 1B |
| 2 | vLLM-SR d3-lite (0.8B) vLLM Semantic RouterOpen weights | 26.2 | 0.094 | 37 ms | — | 853M |
| 3 | jiwo 0.8B v2 eljiwoOpen weights | 25.8 | 0.068 | 36 ms | — | 752M |
| 4 | Saina Helm 2.0 SainaOpen weights | 25.3 | 0.168 | 39 ms | — | 853M |
| 5 | crivo-400m tardellirsOpen weights | 23.7 | 0.121 | 17 ms | — | 396M |
| 6 | Sieve 0.8B Sthānika AIOpen weights | 20.8 | 0.088 | 52 ms | — | 590M |
| 7 | EXAONE-4.0-1.2B-JEV v0.3 carrtesyOpen weights | 20.6 | 0.079 | 149 ms | — | 1B |
| 8 | tasksource Decider nano v4 (150M) tasksourceOpen weights | 19.9 | 0.070 | 13 ms | — | 149M |
| 9 | vLLM-SR Decision 2.0 Eos 0.8B vLLM Semantic RouterOpen weights | 18.4 | 0.130 | 25 ms | — | 870M |
| 10 | Crivo-150M tardellirsOpen weights | 18.3 | 0.115 | 13 ms | — | 150M |
| 11 | Bekko System One v0 400M hotchpotchOpen weights | 18.0 | 0.111 | 17 ms | — | 400M |
| 12 | vLLM-SR d3-edge (0.6B) vLLM Semantic RouterOpen weights | 17.7 | 0.141 | 19 ms | — | 594M |
| 13 | DecisionTune 1.0 DecisionTuneOpen weights | 17.2 | 0.147 | 14 ms | — | 395M |
| 14 | Valen-0.8B Valen-TeamOpen weights | 16.6 | 0.108 | 128 ms | — | 854M |
| 15 | vLLM-SR Decision 2.0 Kai 0.6B vLLM Semantic RouterOpen weights | 16.4 | 0.038 | 19 ms | — | 600M |
| 16 | Kev 0.8B r15 Jared PalmerOpen weights | 16.3 | 0.040 | 45 ms | — | 870M |
| 17 | JPT-0.8B kirpOpen weights | 15.5 | 0.069 | 118 ms | — | 873M |
| 18 | jev-ettin-400m-20261013-v0 ElfsongOpen weights | 15.2 | 0.090 | 16 ms | — | 400M |
| 19 | Sifr 0.8B v3.1 mohamedlotfy50Open weights | 14.5 | 0.120 | 35 ms | — | 870M |
| 20 | Crivo-32M tardellirsOpen weights | 14.2 | 0.133 | 8 ms | — | 32M |
| 21 | Dinah-0 LukitaduarteOpen weights | 13.9 | 0.104 | 14 ms | — | 150M |
| 22 | Intern-Decision-0.8B Intern Large ModelsOpen weights | 12.7 | 0.025 | 34 ms | — | 873M |
| 23 | Jev-Style 0.8B v3 chaoliangUNSWOpen weights | 12.5 | 0.084 | 36 ms | — | 870M |
| 24 | Tev1-0.8B-experimental TogetherOpen weights | 12.5 | 0.126 | 29 ms | — | 873M |
| 25 | Bekko System One v0 68M hotchpotchOpen weights | 12.4 | 0.113 | 12 ms | — | 68M |
Scores, calibration (ECE) and latency from the Jev Decision Index; cost per 1,000 decisions at 200 input tokens each. Updated daily.
More decision-model rankings
Frequently asked questions
What is the best decision model that runs on a CPU?
OneJev1.5-0.8B ranks first among CPU-class decision models on the Jev Decision Index.
How accurate are CPU decision models compared with large ones?
They trail the 27B-class leaders by a wide margin on the Decision Index, but answer in milliseconds on commodity hardware, which suits high-volume routing and filtering.