Multimodal · Benchmark profile

Liquid image-to-JSON extraction JSON validity

A display-only Liquid AI extraction metric measuring the share of image-to-JSON outputs that parse as strict JSON.

Reference2026Active2 models

Data verified 1 Aug 2026 · Methodology 2.3.0

Benchmark score on Liquid image-to-JSON extraction JSON validity

Leaderboard · 2 models

LFM2.5-VL-1.6B-Extract leads at 99.6%, followed by LFM2.5-VL-450M-Extract (98.9%).

Display onlyMultimodal2026

#1Open

LFM2.5-VL-1.6B-Extract

LiquidAI

lfm2-5-vl-1-6b-extract

99.6%

Overall — · Context 128K tokens

#2Open

LFM2.5-VL-450M-Extract

LiquidAI

lfm2-5-vl-450m-extract

98.9%

Overall — · Context 128K tokens

ViewModelsColours

LiquidAI

Lumina

Liquid image-to-JSON extraction JSON validity leaderboard

Accessible data for Liquid image-to-JSON extraction JSON validity leaderboard
Model	Rank	Model ID	Provider	Score	Unit
LFM2.5-VL-1.6B-Extract	#1	lfm2-5-vl-1-6b-extract	LiquidAI	99.6	percent
LFM2.5-VL-450M-Extract	#2	lfm2-5-vl-450m-extract	LiquidAI	98.9	percent

Benchmark score table (2 models)

One best compatible score per canonical product · higher is better

Liquid image-to-JSON extraction JSON validity leaderboard ranked by score
Rank	Model	Provider	License	Evidence use	Score
#1	LFM2.5-VL-1.6B-Extract lfm2-5-vl-1-6b-extract	LiquidAI	open	Source carrier	99.6%
#2	LFM2.5-VL-450M-Extract lfm2-5-vl-450m-extract	LiquidAI	open	Source carrier	98.9%

Configuration-preserving evidencePublished source rows (6)Exact source labels, configurations, versions and dated observations. Same-snapshot canonical/configuration projections are shown once.

Every distinct dated source-published row for Liquid image-to-JSON extraction JSON validity, including exact model configuration labels
Exact published model / configuration	Canonical product	Score	Version / system	Evidence	Source / observed
Exact BenchLM registry variant LFM2.5-VL-1.6B-Extract; bulk export does not retain a complete upstream harness configuration. source label without registered configuration ID	LFM2.5-VL-1.6B-Extract	99.6%	2026Source-native system	Source carrier · no additional scoring weight source-checked	BenchLM public datasets — 2026-08-01 ↗Observed 2026-08-01 · checked 2026-08-01
Exact BenchLM registry variant LFM2.5-VL-450M-Extract; bulk export does not retain a complete upstream harness configuration. source label without registered configuration ID	LFM2.5-VL-450M-Extract	98.9%	2026Source-native system	Source carrier · no additional scoring weight source-checked	BenchLM public datasets — 2026-08-01 ↗Observed 2026-08-01 · checked 2026-08-01
Exact BenchLM registry variant LFM2.5-VL-1.6B-Extract; bulk export does not retain a complete upstream harness configuration. source label without registered configuration ID	LFM2.5-VL-1.6B-Extract	99.6%	2026Source-native system	Source carrier · no additional scoring weight source-checked	BenchLM public datasets — 2026-07-27 ↗Observed 2026-07-27 · checked 2026-07-27
Exact BenchLM registry variant LFM2.5-VL-450M-Extract; bulk export does not retain a complete upstream harness configuration. source label without registered configuration ID	LFM2.5-VL-450M-Extract	98.9%	2026Source-native system	Source carrier · no additional scoring weight source-checked	BenchLM public datasets — 2026-07-27 ↗Observed 2026-07-27 · checked 2026-07-27
Exact BenchLM registry variant LFM2.5-VL-1.6B-Extract; bulk export does not retain a complete upstream harness configuration. source label without registered configuration ID	LFM2.5-VL-1.6B-Extract	99.6%	2026Source-native system	Source carrier · no additional scoring weight source-checked	BenchLM public datasets — 21 July 2026 ↗Observed 2026-07-21 · checked 2026-07-21
Exact BenchLM registry variant LFM2.5-VL-450M-Extract; bulk export does not retain a complete upstream harness configuration. source label without registered configuration ID	LFM2.5-VL-450M-Extract	98.9%	2026Source-native system	Source carrier · no additional scoring weight source-checked	BenchLM public datasets — 21 July 2026 ↗Observed 2026-07-21 · checked 2026-07-21

Compare top models

LFM2.5-VL-1.6B-Extract vs LFM2.5-VL-450M-Extract

About Liquid image-to-JSON extraction JSON validity

Definition and scoring

Organisation: Liquid AI
Category: Multimodal
Version: 2026
Direction: higher is better
Ranking use: Reference
Contamination risk: Unknown

A display-only Liquid AI extraction metric measuring the share of image-to-JSON outputs that parse as strict JSON. Every genuine source row stays tied to its exact model label, configuration, benchmark version and evaluation system. The summary chart shows one best compatible score per canonical product; Score 2.0 admits only explicitly mapped, frozen protocols and keeps incompatible configurations separate.

Open benchmark source ↗

FAQ

Quick answers

What does Liquid image-to-JSON extraction JSON validity measure?

A display-only Liquid AI extraction metric measuring the share of image-to-JSON outputs that parse as strict JSON.

Which model scores highest on Liquid image-to-JSON extraction JSON validity?

LFM2.5-VL-1.6B-Extract by LiquidAI currently leads with 99.6%.

How many models are evaluated on Liquid image-to-JSON extraction JSON validity?

2 canonical model products have a qualifying score, backed by 6 distinct dated source rows.

Multimodal · Benchmark profile

Liquid image-to-JSON extraction JSON validity

A display-only Liquid AI extraction metric measuring the share of image-to-JSON outputs that parse as strict JSON.

Reference2026Active2 models

Data verified 1 Aug 2026 · Methodology 2.3.0

Benchmark score on Liquid image-to-JSON extraction JSON validity

Leaderboard · 2 models

LFM2.5-VL-1.6B-Extract leads at 99.6%, followed by LFM2.5-VL-450M-Extract (98.9%).

Display onlyMultimodal2026

#1Open

LFM2.5-VL-1.6B-Extract

LiquidAI

lfm2-5-vl-1-6b-extract

99.6%

Overall — · Context 128K tokens

#2Open

LFM2.5-VL-450M-Extract

LiquidAI

lfm2-5-vl-450m-extract

98.9%

Overall — · Context 128K tokens

ViewModelsColours

LiquidAI

Lumina

Liquid image-to-JSON extraction JSON validity leaderboard

Accessible data for Liquid image-to-JSON extraction JSON validity leaderboard
Model	Rank	Model ID	Provider	Score	Unit
LFM2.5-VL-1.6B-Extract	#1	lfm2-5-vl-1-6b-extract	LiquidAI	99.6	percent
LFM2.5-VL-450M-Extract	#2	lfm2-5-vl-450m-extract	LiquidAI	98.9	percent

Benchmark score table (2 models)

One best compatible score per canonical product · higher is better

Liquid image-to-JSON extraction JSON validity leaderboard ranked by score
Rank	Model	Provider	License	Evidence use	Score
#1	LFM2.5-VL-1.6B-Extract lfm2-5-vl-1-6b-extract	LiquidAI	open	Source carrier	99.6%
#2	LFM2.5-VL-450M-Extract lfm2-5-vl-450m-extract	LiquidAI	open	Source carrier	98.9%

Configuration-preserving evidencePublished source rows (6)Exact source labels, configurations, versions and dated observations. Same-snapshot canonical/configuration projections are shown once.

Every distinct dated source-published row for Liquid image-to-JSON extraction JSON validity, including exact model configuration labels
Exact published model / configuration	Canonical product	Score	Version / system	Evidence	Source / observed
Exact BenchLM registry variant LFM2.5-VL-1.6B-Extract; bulk export does not retain a complete upstream harness configuration. source label without registered configuration ID	LFM2.5-VL-1.6B-Extract	99.6%	2026Source-native system	Source carrier · no additional scoring weight source-checked	BenchLM public datasets — 2026-08-01 ↗Observed 2026-08-01 · checked 2026-08-01
Exact BenchLM registry variant LFM2.5-VL-450M-Extract; bulk export does not retain a complete upstream harness configuration. source label without registered configuration ID	LFM2.5-VL-450M-Extract	98.9%	2026Source-native system	Source carrier · no additional scoring weight source-checked	BenchLM public datasets — 2026-08-01 ↗Observed 2026-08-01 · checked 2026-08-01
Exact BenchLM registry variant LFM2.5-VL-1.6B-Extract; bulk export does not retain a complete upstream harness configuration. source label without registered configuration ID	LFM2.5-VL-1.6B-Extract	99.6%	2026Source-native system	Source carrier · no additional scoring weight source-checked	BenchLM public datasets — 2026-07-27 ↗Observed 2026-07-27 · checked 2026-07-27
Exact BenchLM registry variant LFM2.5-VL-450M-Extract; bulk export does not retain a complete upstream harness configuration. source label without registered configuration ID	LFM2.5-VL-450M-Extract	98.9%	2026Source-native system	Source carrier · no additional scoring weight source-checked	BenchLM public datasets — 2026-07-27 ↗Observed 2026-07-27 · checked 2026-07-27
Exact BenchLM registry variant LFM2.5-VL-1.6B-Extract; bulk export does not retain a complete upstream harness configuration. source label without registered configuration ID	LFM2.5-VL-1.6B-Extract	99.6%	2026Source-native system	Source carrier · no additional scoring weight source-checked	BenchLM public datasets — 21 July 2026 ↗Observed 2026-07-21 · checked 2026-07-21
Exact BenchLM registry variant LFM2.5-VL-450M-Extract; bulk export does not retain a complete upstream harness configuration. source label without registered configuration ID	LFM2.5-VL-450M-Extract	98.9%	2026Source-native system	Source carrier · no additional scoring weight source-checked	BenchLM public datasets — 21 July 2026 ↗Observed 2026-07-21 · checked 2026-07-21

Compare top models

LFM2.5-VL-1.6B-Extract vs LFM2.5-VL-450M-Extract

About Liquid image-to-JSON extraction JSON validity

Definition and scoring

Organisation: Liquid AI
Category: Multimodal
Version: 2026
Direction: higher is better
Ranking use: Reference
Contamination risk: Unknown

Open benchmark source ↗

FAQ

Quick answers

What does Liquid image-to-JSON extraction JSON validity measure?

A display-only Liquid AI extraction metric measuring the share of image-to-JSON outputs that parse as strict JSON.

Which model scores highest on Liquid image-to-JSON extraction JSON validity?

LFM2.5-VL-1.6B-Extract by LiquidAI currently leads with 99.6%.

How many models are evaluated on Liquid image-to-JSON extraction JSON validity?

2 canonical model products have a qualifying score, backed by 6 distinct dated source rows.

Navigation

Liquid image-to-JSON extraction JSON validity

Leaderboard · 2 models

LFM2.5-VL-1.6B-Extract

LFM2.5-VL-450M-Extract

Liquid image-to-JSON extraction JSON validity leaderboard

Crop Liquid image-to-JSON extraction JSON validity leaderboard

Benchmark score table (2 models)

Crop Liquid image-to-JSON extraction JSON validity benchmark table

Crop Liquid image-to-JSON extraction JSON validity published source rows

Compare top models

Definition and scoring

Quick answers

What does Liquid image-to-JSON extraction JSON validity measure?

Which model scores highest on Liquid image-to-JSON extraction JSON validity?

How many models are evaluated on Liquid image-to-JSON extraction JSON validity?

Liquid image-to-JSON extraction JSON validity

Leaderboard · 2 models

LFM2.5-VL-1.6B-Extract

LFM2.5-VL-450M-Extract

Liquid image-to-JSON extraction JSON validity leaderboard

Crop Liquid image-to-JSON extraction JSON validity leaderboard

Benchmark score table (2 models)

Crop Liquid image-to-JSON extraction JSON validity benchmark table

Crop Liquid image-to-JSON extraction JSON validity published source rows

Compare top models

Definition and scoring

Quick answers

What does Liquid image-to-JSON extraction JSON validity measure?

Which model scores highest on Liquid image-to-JSON extraction JSON validity?

How many models are evaluated on Liquid image-to-JSON extraction JSON validity?

Leaderboard · 2 models

LFM2.5-VL-1.6B-Extract

LFM2.5-VL-450M-Extract

Benchmark score table (2 models)

Compare top models

Definition and scoring

Quick answers

What does Liquid image-to-JSON extraction JSON validity measure?

Which model scores highest on Liquid image-to-JSON extraction JSON validity?

How many models are evaluated on Liquid image-to-JSON extraction JSON validity?

More Multimodal benchmarks

Leaderboard · 2 models

LFM2.5-VL-1.6B-Extract

LFM2.5-VL-450M-Extract

Benchmark score table (2 models)

Compare top models

Definition and scoring

Quick answers

What does Liquid image-to-JSON extraction JSON validity measure?

Which model scores highest on Liquid image-to-JSON extraction JSON validity?

How many models are evaluated on Liquid image-to-JSON extraction JSON validity?

More Multimodal benchmarks