Text / openjev

openjev

OpenJev is an open-weights decision model for typed zero-shot classification over text, web pages, and screenshots. It accepts labels at request time and produces choices, yes/no probabilities, or scores without free-form generation. The model supports multiple languages including English, German, French, Hindi, Chinese, and Japanese. Reported latency is about 80 ms for a short text decision and about 210 ms for an isolated web decision on one H100 under specified conditions.

EstimatedRepository opened Sep 20, 2026Source checked 9/23/2026Version: 5ec9e5fd

LOCALRENTED GPUOPEN WEIGHTS

Freshness 83 out of 100. Repository age: 49 days old, Sep 20, 2026. Measures age, not quality.

Popularity 55 out of 100. 9,770 downloads in 30 days; 188 lifetime likes. Checked Nov 7, 2026. Measures adoption, not quality.

What do these scores mean?

Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.

Freshness · release age

A new release starts at 100. The score halves every 180 days: 100 × 2^(−age in days / 180). When the release date is unavailable, a repository date is a fallback—not proof of when the model was released. Missing dates stay unscored.

Check the date source

Popularity · adoption

Downloads over the past 30 days carry 80% of the score; lifetime likes carry 20%. Both use a logarithmic scale, capped at 10 million downloads and 100,000 likes. If likes are unavailable, downloads carry all the weight. Missing download statistics stay unscored.

round(80 × min(1, log10(1 + downloads) / 7) + 20 × min(1, log10(1 + likes) / 5))

Check the statistics source

Scores as of Nov 8, 2026. Statistics checked Nov 7, 2026. Statistics are marked for refresh after 72 hours.Full scoring method

At a glance

Parameters: 27.36B
Architecture: qwen3_5
License: cc-by-nc-4.0
Disk space: 51 GB
Software: vLLM

View the model source

MY HARDWARE

Will it run on your machine?

Save your machine to see a personalized rating and its reasoning.

Add my hardware

Best for

Routing and triage decisions such as intent, topic, team, priority, or language
Moderation and safety decisions such as toxicity, spam, hate, policy violation, or legal threat
Judging other model outputs for groundedness, hallucination, answer quality, or rubric adherence
Documents and operations decisions such as invoice approve/hold/reject, alert severity, or contract clause type
Browser and desktop agent decisions such as which element, which operation, task completion, or blockage

Tradeoffs

Licensed under CC-BY-NC-4.0, which restricts commercial use
Reported latency and accuracy figures are from specific configurations and were not independently tested here
Up to 52 options per question; exceeding this may require different handling
Requires fixed calibration settings for probability conversion
Trained or evaluated on specific datasets; not guaranteed to generalize to all domains or languages

Ways to run it

vLLM · Linux

Repository-specific command in publisher documentation; confirm dependencies and hardware in the source.

vllm serve ./openjev --host 127.0.0.1 --served-model-name qwen --port 8000  --enable-prefix-caching --max-model-len 16384 --gpu-memory-utilization 0.90  --limit-mm-per-prompt '{"image":1}' --trust-remote-code --max-num-seqs 256  --max-logprobs 64 --gdn-prefill-backend triton --quantization fp8

Official instructions

Explore its uses

SAFETENSORSZERO-SHOT-CLASSIFICATION

Keep exploring

Text

Prism ML

Bonsai 2 · 27B

A compressed 27B-class reasoning model with publisher-provided GGUF packs and a dedicated llama.cpp fork for CUDA, Metal, and CPU.

Freshness 82 out of 100. Release age: 52 days old, Sep 17, 2026. Measures age, not quality.

MODEL SIZE27.36B

LOCALRENTED GPU

Released Sep 17, 2026

Text

DeepSeek

DeepSeek V4.1 Flash

An open-weight model for reasoning, coding, agents, and image understanding. DeepSeek V4.1 Flash combines a 552B backbone with sparse activation and up to one million tokens of context. Choose the original checkpoint or a community uncensored variant below.

Freshness 80 out of 100. Repository age: 59 days old, Sep 10, 2026. Measures age, not quality.

MODEL SIZE552B backbone · 8B active prefill / 16B active decode

LOCALRENTED GPU

Repository opened Sep 10, 2026

Text

Qwen

Qwen3.8

Explore 4 versions of Qwen3.8. Compare model sizes, packages, hardware requirements, and available setups.

4 versionsCompare sizes & formats

LOCALRENTED GPU

Compare versions →