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vev

Jev-like decision models that can also see images — open weights on Qwen3.5, run on your own GPU

This is 1 of 255 launches in decision model runtimes and tooling — see how it stacks up on momentum and crowding →

888 other launches read as similar to this one →

Details

External ID
1397876964
Source
GITHUB
Company
—
Product
vev
Website domain
huggingface.co
Launched
Sept. 30, 2026
Cohort
—
Upvotes
8
Upvotes percentile
0.14358128740686454
Tags
classification, decision-model, jev, judgment-model, systemone, typesafe-jev, vision-jev, vision-language-model
Fetched at
Oct. 2, 2026, 1:02 a.m.
Updated at
Oct. 2, 2026, 1:02 a.m.

Enrichment

Theme
decision model runtimes and tooling
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
multimodal decision models for developers
Manually corrected
False

Could you build this?

No Training vision-language decision models with custom KL-anchoring requires novel ML research, bespoke decision datasets, and substantial GPU cluster compute that vibe coding cannot provide.

What it would actually take: Built using PyTorch, Hugging Face transformers, and distributed training frameworks like DeepSpeed or Megatron-LM to fine-tune Qwen 2.5/3.5 VL models. The critical challenges are designing the decision-space formulation, engineering multimodal trajectory datasets, and tuning KL-divergence penalty training to prevent policy collapse. This demands specialized PhD-level machine learning research expertise and significant multi-GPU compute budgets.

Competitors

Other products that read as similar to this one — 888 launches clear the similarity bar, closest 8 shown.

Attention rank: #686 of 889 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 334 days after the earliest competitor.

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