dnotitia
DNA-VL-STEER-2B is a language-bias–calibrated variant of Qwen/Qwen3-VL-Embedding-2B. It keeps everything that makes the base model good — the same architecture, the same 2048-dim shared image/text/video embedding space, the same instruction-aware interface — and closes most of the cross-lingual retrieval gap:...
Running this yourself: can likely run on your own machine.
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Quality Score
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Arena ELO
2B
Parameters
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Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
12 of 22 public signals
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3.0K
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10
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Jul 2026
Released
4/5 signals
0/4 signals
3/5 signals
3/4 signals
2/4 signals
Parameters
2B
Training compute
Not reported
Dataset scale
Not reported
Base model
Not reported
Gaps we are still tracking
Metadata sources
This section gives the plain-English basics first: what the model is, how large it is, how much context it can handle, and whether it is still actively supported.
This tells you how you can use the model in practice: whether weights are open, whether an API exists, and what kinds of input or output it supports.
Capabilities