Decision Models (@DecisionModels) profile picture

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
You want to use Jev but they don't offer it GDPR compliant and hosted in EU 🇪🇺? Consider REAX 1.3, our own model, which is #1 in the Hugging Face Decision Index 0.4.1. (Jev is #12) We also offer mammoth-1 (as s1-pro-5), which leads the public-only ranking. Available via our Jev-compatible API at decisionmodels.io huggingface.co/spaces/multim…
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REAX 1.3, our own model, is #1 on the Hugging Face Decision Index 0.4.1. And mammoth-1, which we serve as s1-pro-5, leads the public-only ranking. Both are live on our Jev-compatible API at decisionmodels.io huggingface.co/spaces/multim…
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REAX 1.3 was built by the miners of Bittensor Subnet 92: two models from our open competition, combined in post-production into one model. Thank you to everyone who mined, tested and pushed the bar. This one is yours.
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REAX 1.3 is live on our API as reax-1.3: EUR 0.40 per million input tokens, output tokens free. Hosted in the EU, Jev-compatible interface. decisionmodels.io/models/rea…
Introducing REAX 1.3 Our new open decision model, built with two models from our Bittensor miner competition and strong open models. Results: our own run on public Hugging Face Decision Index items. Available via API at decisionmodels.io
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We now finally have the @DecisionModels X handle. (formerly we had @decisiomodels_ with an underscore)
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Need decision models without your data leaving the EU? Our EU tier: • EU requests always stay in the EU • Priority on our EU capacity • Never sent to the peer-to-peer network • Prompts and answers not stored or used for training • DPA included decisionmodels.io/eu
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Decision Models is now on New York Token Exchange and @TrustedRouter 🤝 nytokenexchange.com decisionmodels.io
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These are our own models, and we will of course serve them at decisionmodels.io. We'll anounce more details soon.
Meet REAX 1, our open decision model built on Perplexity Decider v1.2. Our own measurement: +2.4 points over its base, ahead in all 6 test draws and all 10 areas. Open competition starts today 13:00 UTC: => Beat it, earn the rewards see reax.co/competitions
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Faster decision models, built in the open: on day one of the REAX engine competition, miners reached nearly 3× the speed of our reference engine.
We asked miners to make our decision model faster. A few hours later: nearly 3×. The REAX engine competition is live on Bittensor SN92.
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The engine inside of decisionmodels.io, and the reason why we most likely can serve these models faster than you may have seen them anywhere else.
The REAX engine serves Perplexity Decider v1.1 up to six (!) times faster than its reference server. Free for individuals and small companies, even commercially. Code in next post. Performance improvement competition opens right now: Beat the s1-fast reference, win the track.
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Use leading Jev class models - blazing fast and - for crazy low prices on decisionmodels.io/
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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…
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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.
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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)
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