LFM2.5-VL-1.6B-Extract
BenchLM is tracking LFM2.5-VL-1.6B-Extract, but this profile is currently excluded from the public leaderboard because it still lacks enough non-generated benchmark coverage to rank safely. Only non-generated public benchmark rows appear below.
LFM2.5-VL-1.6B-Extract is a open weight model with a 128K token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.
LFM2.5-VL-1.6B-Extract sits inside the LFM2.5-VL Extract family alongside LFM2.5-VL-450M-Extract. This profile currently has 3 of 236 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Ranking Distribution
Category rank across 0 benchmark categories — sorted by best rank
Category Performance
Scores across all benchmark categories (0-100 scale)
Category Breakdown
Agentic
Coding
Reasoning
Knowledge
Math
Multilingual
Multimodal
Inst. Following
Benchmark Details
Only benchmark rows with an attached exact-source record are shown here. Source-unverified manual rows and generated rows are hidden from model pages.
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Frequently Asked Questions
How does LFM2.5-VL-1.6B-Extract perform overall in AI benchmarks?
LFM2.5-VL-1.6B-Extract has 3 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.
Is LFM2.5-VL-1.6B-Extract good for multimodal and grounded tasks?
LFM2.5-VL-1.6B-Extract has visible benchmark coverage in multimodal and grounded tasks, but BenchLM does not currently assign it a global category rank there.
Is LFM2.5-VL-1.6B-Extract open source?
Yes, LFM2.5-VL-1.6B-Extract is an open weight model created by LiquidAI, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Which sibling models are related to LFM2.5-VL-1.6B-Extract?
LFM2.5-VL-1.6B-Extract belongs to the LFM2.5-VL Extract family. Related variants on BenchLM include LFM2.5-VL-450M-Extract.
Does LFM2.5-VL-1.6B-Extract have full benchmark coverage on BenchLM?
Not yet. LFM2.5-VL-1.6B-Extract currently has 3 published benchmark scores out of the 236 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
What is the context window size of LFM2.5-VL-1.6B-Extract?
LFM2.5-VL-1.6B-Extract has a context window of 128K, which determines how much text it can process in a single interaction.
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