Liquid image-to-JSON extraction VLM judge score (Liquid Extract VLM Judge)
We show this table for reference; we do not rank on it.
A display-only Liquid AI extraction metric measuring judged agreement between extracted values and the source image.
Benchmark score on Liquid Extract VLM Judge — September 27, 2026
We compile the Liquid Extract VLM Judge rows from provider self-reports. LFM2.5-VL-1.6B-Extract leads the table at 90.6%, followed by LFM2.5-VL-450M-Extract (84.5%). We do not use these results to rank models overall.
LFM2.5-VL-1.6B-Extract
LiquidAI
LFM2.5-VL-450M-Extract
LiquidAI
2 modelsMultimodal & GroundedCurrentDisplay onlyUpdated September 27, 2026
Benchmark score table (2 models)
ScoreAbout Liquid Extract VLM Judge
Year
2026
Tasks
Image-to-JSON extraction
Format
VLM-judged extraction accuracy
Difficulty
Structured visual extraction
Liquid reports VLM Judge Score using a separate vision model to compare extracted JSON content against the image. BenchLM stores it as a specialized visual extraction quality signal.
Freshness and provenance
Version
Liquid Extract VLM Judge 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
Questions
What does Liquid Extract VLM Judge measure?
A display-only Liquid AI extraction metric measuring judged agreement between extracted values and the source image.
Which model scores highest on Liquid Extract VLM Judge?
LFM2.5-VL-1.6B-Extract by LiquidAI currently leads with a score of 90.6% on Liquid Extract VLM Judge.
How many models are evaluated on Liquid Extract VLM Judge?
2 AI models have been evaluated on Liquid Extract VLM Judge on BenchLM.
Compare top models on Liquid Extract VLM Judge
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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