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LFM2.5-ColBERT-350M

LiquidAICurrentReleased Jun 18, 2026
Overall Score
Unranked
Arena Elo
N/A
Categories Ranked
0of 8
Price (1M tokens)
$0 in / $0 out
Speed
N/A
Context
32K
Open WeightSelf-hostNon-Reasoning
Confidence
colbert

BenchLM is tracking LFM2.5-ColBERT-350M, 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-ColBERT-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.

LFM2.5-ColBERT-350M sits inside the LFM2.5 Retrievers family alongside LFM2.5-Embedding-350M. This profile currently has 2 of 249 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

No ranking data available

Category Performance

Scores across all benchmark categories (0-100 scale)

Category Breakdown

Agentic

0.0/ 100
Weight: 22%0 benchmarks
Terminal-Bench 2.0BrowseCompOSWorld-VerifiedGAIATAU-benchWebArena

Coding

0.0/ 100
Weight: 20%0 benchmarks
SWE-bench VerifiedLiveCodeBenchSWE-bench ProSWE-RebenchSciCode

Reasoning

0.0/ 100
Weight: 17%0 benchmarks
MuSRLongBench v2MRCRv2ARC-AGI-2

Knowledge

0.0/ 100
Weight: 12%0 benchmarks
GPQASuperGPQAMMLU-ProHLEFrontierScienceSimpleQA

Math

0.0/ 100
Weight: 5%0 benchmarks
AIME 2025BRUMO 2025MATH-500FrontierMath

Multilingual

0.0/ 100
Weight: 7%2 benchmarks
MGSMMMLU-ProX

Multimodal

0.0/ 100
Weight: 12%0 benchmarks
MMMU-ProOfficeQA ProCharXivCharXiv w/o tools

Inst. Following

0.0/ 100
Weight: 5%0 benchmarks
IFEvalIFBench

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.

LFM2.5 Retrievers Family

Colbert

Canonical Entry

LFM2.5-Embedding-350M

Frequently Asked Questions

How does LFM2.5-ColBERT-350M perform overall in AI benchmarks?

LFM2.5-ColBERT-350M has 2 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.

Is LFM2.5-ColBERT-350M good for multilingual tasks?

LFM2.5-ColBERT-350M has visible benchmark coverage in multilingual tasks, but BenchLM does not currently assign it a global category rank there.

Is LFM2.5-ColBERT-350M open source?

Yes, LFM2.5-ColBERT-350M 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-ColBERT-350M?

LFM2.5-ColBERT-350M belongs to the LFM2.5 Retrievers family. Related variants on BenchLM include LFM2.5-Embedding-350M.

Does LFM2.5-ColBERT-350M have full benchmark coverage on BenchLM?

Not yet. LFM2.5-ColBERT-350M currently has 2 published benchmark scores out of the 249 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-ColBERT-350M?

LFM2.5-ColBERT-350M has a context window of 32K, which determines how much text it can process in a single interaction.

Last updated: June 18, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

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