GLiNER 2-XL is here
State of the art classification and NER all in one model
First 1000 requests free
Efficiency at Scale
New capabilities with GliNER-2
Named Entity Recognition
Identify people, companies, locations, and concepts in any text — instantly.
GLiNER 2-XL uses zero-shot transfer and contextual embeddings to detect new entities with human-level precision, without retraining.
Text Classification
Understand intent, sentiment, and topic at scale.
Classify messages, documents, or conversations into fine-grained categories that evolve with your users — powered by adaptive, self-learning agents.
Structured Extraction
Turn unstructured text into clean, actionable data.
Automatically extract key fields like amounts, addresses, or events, and map them into your database or workflow — ready for analytics, automation, or compliance.
GliNER-2-XL NER Benchmark Results
Dataset | GPT-5 | GLiNER-M | GLiNER-2-XL |
|---|---|---|---|
Parameters | - | 209M | 1B |
Hosting | - | Self-host | Fastino hosted (A100) |
Latency | 7000-28000 ms | 160 ms | 130 ms |
CrossNER - AI | 0.547 | 0.518 | 0.573 |
CrossNER - Literature | 0.561 | 0.597 | 0.572 |
CrossNER - Music | 0.736 | 0.694 | 0.717 |
CrossNER - Politics | 0.632 | 0.686 | 0.675 |
CrossNER - Science | 0.518 | 0.581 | 0.623 |
CrossNER - Average | 0.599 | 0.615 | 0.636 |