Tiger Lab model product
VLM2Vec-LoRA is an embedding model from Tiger Lab ranked in MTEB.
Updated Oct 23, 2026. Default version: VLM2Vec-LoRA
This profile uses the model's current scored version. Arena ratings and prices are shown separately.
Benchmark scores for VLM2Vec-LoRA.
Benchmark | Score | Rank | Participants | Percentile | Evidence | Evaluated |
|---|
| BenchmarkMIEB English Semantic Similarity | Score53.60% | Rank21 | Participants50 | Percentile59.18% | EvidenceA | EvaluatedN/A |
| BenchmarkMIEB English Clustering | Score72.64% | Rank37 | Participants49 | Percentile25.00% | EvidenceA | EvaluatedN/A |
| BenchmarkMIEB English Classification | Score54.12% | Rank46 | Participants49 | Percentile6.25% | EvidenceA | EvaluatedN/A |
| BenchmarkMIEB English Multimodal | Score38.70% | Rank60 | Participants88 | Percentile32.18% | EvidenceA | EvaluatedN/A |
Preference and agent-evaluation results for the default version.
The default version does not have a matching Arena result yet.
Official vendor API pricing appears first, followed by individual provider offers.
The default version has no current input or output token prices.
Official prices use only the vendor's configured official Provider and positive standard USD PAYG rates. Third-party offers remain explicitly labeled.
Provider-specific output speed and catalog latency for VLM2Vec-LoRA. Runtime does not affect the capability score.
No provider-specific speed or latency record is linked to the default version yet.
Output Speed is generated output tokens received per second. Catalog latency is reported separately from observed provider TTFT.
Technical details for the model's default version.
Available versions of this model. The score column identifies the version used in the overall ranking.
Version | Released | LLMBoard | Parameters | Context | Max output | Open weights | License |
|---|
| VersionVLM2Vec-LoRA | Released | LLMBoard41.05 | Parameters4.2B | Context131.1K | Max outputN/A | Open weightsYes | Licenseapache-2.0 |
Recommendations prioritize the same model type and family, then the closest LLMBoard score.
Key information about VLM2Vec-LoRA and its available data.
VLM2Vec-LoRA is an embedding model from Tiger Lab. It is a ranked model from MTEB.
Data as of 2026-10-22.
Common questions about VLM2Vec-LoRA.
VLM2Vec-LoRA's default version was released on Oct 8, 2024.
No official standard PAYG price is currently available for VLM2Vec-LoRA.
VLM2Vec-LoRA was created by Tiger Lab.
The default version has a 131.1K token context window.
Yes. The default version is marked as open weight under apache-2.0.
No provider offering is currently linked to the default version.