Model profile
LFM2.5-VL-450M-Extract
Evidence coverage
3 of 323 tracked benchmarks are published. 3 are verified and 0 provisional. 1 of 8 categories are measured.
- Published / tracked
- 3 / 323
- Verified
- 3
- Provisional
- 0
- Categories with evidence
- 1 / 8
Evidence by category
- Agentic0 benchmarksNot measured
- Coding0 benchmarksNot measured
- Reasoning0 benchmarksNot measured
- Knowledge0 benchmarksNot measured
- Math0 benchmarksNot measured
- Multilingual0 benchmarksNot measured
- Multimodal3 benchmarksVerified
- Inst. Following0 benchmarksNot measured
BenchLM is tracking LFM2.5-VL-450M-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-450M-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-450M-Extract sits inside the LFM2.5-VL Extract family alongside LFM2.5-VL-1.6B-Extract. This profile currently has 3 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-450M-ExtractCurrent modelLiquidAIUnrankedNot measuredLFM2.5-VL-450M-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%0 benchmarksNot measured | Not measured | Not ranked | Not available | 22% | 0 benchmarks | Not measured |
| CodingWeight 20%0 benchmarksNot measured | Not measured | Not ranked | Not available | 20% | 0 benchmarks | Not measured |
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | Not ranked | Not available | 17% | 0 benchmarks | Not measured |
| KnowledgeWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| 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%3 benchmarksVerified | Score pending | Not ranked | Not available | 12% | 3 benchmarks | Verified |
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
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.
Multimodal3 benchmarks
Liquid image-to-JSON extraction JSON validity
Liquid image-to-JSON extraction schema consistency F1
Liquid image-to-JSON extraction VLM judge score
Frequently Asked Questions
How does LFM2.5-VL-450M-Extract perform overall in AI benchmarks?
LFM2.5-VL-450M-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-450M-Extract good for multimodal and grounded tasks?
LFM2.5-VL-450M-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-450M-Extract open source?
Yes, LFM2.5-VL-450M-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-450M-Extract?
LFM2.5-VL-450M-Extract belongs to the LFM2.5-VL Extract family. Related variants on BenchLM include LFM2.5-VL-1.6B-Extract.
Does LFM2.5-VL-450M-Extract have full benchmark coverage on BenchLM?
Not yet. LFM2.5-VL-450M-Extract currently has 3 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-450M-Extract?
LFM2.5-VL-450M-Extract has a published context window of 128K, which determines how much text it can process in a single interaction.
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