LFM2.5-8B-A1B
BenchLM is tracking LFM2.5-8B-A1B, 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.
LFM2.5-8B-A1B is a open weight model with a 128K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.
This profile currently has 9 of 224 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Its strongest category is Instruction Following (#58), while its weakest is Mathematics (#65). This performance profile makes it a well-rounded choice across a range of tasks.
Ranking Distribution
Category rank across 2 benchmark categories — sorted by best rank
Category Performance
Scores across all benchmark categories (0-100 scale)
Category Breakdown
Agentic
Coding
Reasoning
Knowledge
Math
#65Multilingual
Multimodal
Inst. Following
#58Benchmark 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.
Compare This Model
See how LFM2.5-8B-A1B stacks up against similar models
Frequently Asked Questions
How does LFM2.5-8B-A1B perform overall in AI benchmarks?
LFM2.5-8B-A1B has 9 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.
Is LFM2.5-8B-A1B good for knowledge and understanding?
LFM2.5-8B-A1B has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is LFM2.5-8B-A1B good for mathematics?
LFM2.5-8B-A1B ranks #65 out of 119 models in mathematics benchmarks with an average score of 36.5. There are stronger options in this category.
Is LFM2.5-8B-A1B good for agentic tool use and computer tasks?
LFM2.5-8B-A1B has visible benchmark coverage in agentic tool use and computer tasks, but BenchLM does not currently assign it a global category rank there.
Is LFM2.5-8B-A1B good for instruction following?
LFM2.5-8B-A1B ranks #58 out of 119 models in instruction following benchmarks with an average score of 63.7. There are stronger options in this category.
Is LFM2.5-8B-A1B open source?
Yes, LFM2.5-8B-A1B is an open weight model created by LiquidAI, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Does LFM2.5-8B-A1B have full benchmark coverage on BenchLM?
Not yet. LFM2.5-8B-A1B currently has 9 published benchmark scores out of the 224 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 LFM2.5-8B-A1B?
LFM2.5-8B-A1B has a context window of 128K, which determines how much text it can process in a single interaction.
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