Model profile
LFM2.5-VL-1.6B-Extract
Evidence coverage
15 of 323 tracked benchmarks are published. 3 are verified and 12 provisional. 6 of 8 categories are measured.
- Published / tracked
- 15 / 323
- Verified
- 3
- Provisional
- 12
- Categories with evidence
- 6 / 8
Evidence by category
- Agentic1 benchmarkReported
- Coding1 benchmarkReported
- Reasoning2 benchmarksReported
- Knowledge6 benchmarksReported
- Math0 benchmarksNot measured
- Multilingual0 benchmarksNot measured
- Multimodal4 benchmarksMixed evidence
- Inst. Following1 benchmarkReported
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 15 of 323 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Peer position
Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.
Range 77.44–83.93
- Claude Mythos 5AnthropicCompare#183.93Claude Mythos 5 is #1 with a score of 83.93.
- Claude Fable 5AnthropicCompare#283.68Claude Fable 5 is #2 with a score of 83.68.
- GPT-5.6 SolOpenAICompare#381.96GPT-5.6 Sol is #3 with a score of 81.96.
- Kimi K3Moonshot AICompare#480.96Kimi K3 is #4 with a score of 80.96.
- Claude Opus 4.8AnthropicCompare#578.34Claude Opus 4.8 is #5 with a score of 78.34.
- Muse Spark 1.1MetaCompare#677.44Muse Spark 1.1 is #6 with a score of 77.44.
- LFM2.5-VL-1.6B-ExtractCurrent modelLiquidAIUnrankedNot measuredLFM2.5-VL-1.6B-Extract is Unranked with a score of Not measured.
Category percentile
More
Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.
Category evidence
Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticWeight 22%1 benchmarkReported | Score pending | Not ranked | Not available | 22% | 1 benchmark | Reported |
| CodingWeight 20%1 benchmarkReported | Score pending | Not ranked | Not available | 20% | 1 benchmark | Reported |
| ReasoningWeight 17%2 benchmarksReported | Score pending | Not ranked | Not available | 17% | 2 benchmarks | Reported |
| KnowledgeWeight 12%6 benchmarksReported | Score pending | Not ranked | Not available | 12% | 6 benchmarks | Reported |
| MathWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalWeight 12%4 benchmarksMixed sources | Score pending | Not ranked | Not available | 12% | 4 benchmarks | Mixed sources |
| Inst. FollowingWeight 5%1 benchmarkReported | Score pending | Not ranked | Not available | 5% | 1 benchmark | Reported |
Benchmark Details
Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.
Agentic1 benchmark
τ²-Bench Tool-Agent-User Evaluation
Coding1 benchmark
Artificial Analysis SciCode
Reasoning2 benchmarks
Artificial Analysis Long Context Reasoning
Critical Physics Tasks
Knowledge6 benchmarks
Artificial Analysis GPQA Diamond
Artificial Analysis Humanity's Last Exam
Artificial Analysis Omniscience Index
Artificial Analysis Omniscience Accuracy
Artificial Analysis Omniscience Hallucination Rate
Multimodal4 benchmarks
Liquid image-to-JSON extraction JSON validity
Liquid image-to-JSON extraction schema consistency F1
Liquid image-to-JSON extraction VLM judge score
Artificial Analysis MMMU-Pro
Inst. Following1 benchmark
Artificial Analysis IFBench
Frequently Asked Questions
How does LFM2.5-VL-1.6B-Extract perform overall in AI benchmarks?
LFM2.5-VL-1.6B-Extract has 15 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 knowledge and understanding?
LFM2.5-VL-1.6B-Extract has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is LFM2.5-VL-1.6B-Extract good for coding and programming?
LFM2.5-VL-1.6B-Extract has visible benchmark coverage in coding and programming, but BenchLM does not currently assign it a global category rank there.
Is LFM2.5-VL-1.6B-Extract good for reasoning and logic?
LFM2.5-VL-1.6B-Extract has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is LFM2.5-VL-1.6B-Extract good for agentic tool use and computer tasks?
LFM2.5-VL-1.6B-Extract 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-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 good for instruction following?
LFM2.5-VL-1.6B-Extract has visible benchmark coverage in instruction following, 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 15 published benchmark scores out of the 323 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 published context window of 128K, which determines how much text it can process in a single interaction.
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