Fast, low-cost open decision models on one Jev-compatible API. Route, score & approve with probabilities. EU-hosted option. Powered by @reaxlabs (SN92).
@reaxlabs
Joined October 2026
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Decision Models retweeted
Introducing REAX, Bittensor subnet 92!
An open network about AI decision models:
- miners host, train and spped-up models
- validators test correctness
- and customers use them through decisionmodels.io
A gaming GPU is enough to join. reax.co
🧵
Introducing DecisionModels @decisionmodels_
I've spent the last four weeks benchmarking decision models (I run JevBench).
Today I'm launching the place to actually use the best ones:
decisionmodels.io
➡️Top open models
➡️Up to 4x faster on our own REAX engine
➡️From $0.019 per 1M input tokens.
Expect more reveals soon, and read 👇
We're releasing s1-llm-auto-router as open weights:
A small decision model that reads a request and picks the right LLM for it.
▸ 26 ms on a CPU, 22 languages, MIT license
▸ Our first use-case-specific decision model, from decisionmodels.io and Bittensor Subnet 92 (REAX)
▸ The best of the decision models we tested for this use case.
▸Now live on decisionmodels.io.
We're also announcing a joint project with msg group:
msg will evaluate the model in an internal project to make its use of LLMs more efficient. msg is one of Germany's top 5 IT consultancies (€1.5B revenue, 10,000+ employees).
Thank you, Dr. Ralf S. Engelschall (@engelschall), CTO of msg and one of the founding members of the Apache Software Foundation.
We believe use-case-specific decision models will become a huge market. More from us soon.
huggingface.co/decisionmodel…
How it compares on our own held-out routing test (2,175 synthetic requests in 22 languages, labels from a 5-LLM consensus, method in the model card):
It picks the same model as the gold label 74% of the time, the best of the decision models we tested, at 26 ms on a CPU.
On JevBench:
As its operator, we never rank our own models there. And a specialist like this isn't a fit for general decision-model benchmarks anyway, so we measured it on the task it was built for.
Hi, we're DecisionModels.
The best open decision models, served fast through one API:
→ s1-pro runs vLLM-SR d3, the most capable decision model in the world *
→ up to 4x faster on our own REAX engine
→ s1-fast from $0.019 per 1M input tokens (about 1.6x cheaper than Jev), output free
→ EU-hosted option with a DPA, built for GDPR and the EU AI Act
decisionmodels.io
* according to both the Decision Index on Hugging Face and the Capability Score on JevBench (our founder's own project)
Served by REAX, an open inference network on Bittensor subnet 92.
A gaming GPU is enough to participate.
reax.co
Decision Models retweeted
Introducing DecisionModels @decisionmodels_
I've spent the last four weeks benchmarking decision models (I run JevBench).
Today I'm launching the place to actually use the best ones:
decisionmodels.io
➡️Top open models
➡️Up to 4x faster on our own REAX engine
➡️From $0.019 per 1M input tokens.
Expect more reveals soon, and read 👇