BenchLM is tracking LFM2.5-350M by LiquidAI. Some benchmark data is visible, but not enough non-generated coverage is available for a leaderboard rank yet.
BenchLM is tracking LFM2.5-350M, but this profile is currently excluded from the public leaderboard because it still lacks enough verified benchmark coverage to rank safely. Only verified public benchmark rows appear below.
LFM2.5-350M is a open weight model with a 32K token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.
This profile currently has 3 of 62 tracked benchmarks. BenchLM only exposes verified benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Its strongest category is Instruction Following (#82). This performance profile makes it a well-rounded choice across a range of tasks.
Provider
LiquidAISource Type
Open WeightReasoning
Non-ReasoningContext Window
32K
Model Status
Current
Release Date
Mar 31, 2026Overall Score
Unranked
Pricing
$0.00 / $0.00
Input / output per 1M
Runtime
N/A
Latency unavailable
BenchLM is still missing enough verified benchmark coverage to rank this model across the public leaderboard. Only verified public benchmark rows are shown below.
LFM2.5-350M has 3 verified benchmark scores on BenchLM, but it does not yet have enough coverage to receive a global overall rank.
LFM2.5-350M has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
LFM2.5-350M ranks #82 out of 97 models in instruction following benchmarks with an average score of 77. There are stronger options in this category.
Yes, LFM2.5-350M is an open weight model created by LiquidAI, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Not yet. LFM2.5-350M currently has 3 verified benchmark scores out of the 62 benchmarks BenchLM tracks. BenchLM only exposes verified public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
LFM2.5-350M has a context window of 32K, which determines how much text it can process in a single interaction.
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