//- 💫 DOCS > USAGE > FACTS & FIGURES > BENCHMARKS > MODEL COMPARISON

p
    |  In this section, we provide benchmark accuracies for the pre-trained
    |  model pipelines we distribute with spaCy. Evaluations are conducted
    |  end-to-end from raw text, with no "gold standard" pre-processing, over
    |  text from a mix of genres where possible.

+under-construction

+aside("Methodology")
    |  The evaluation was conducted on raw text with no gold standard
    |  information. The parser, tagger and entity recognizer were trained on the
    |  #[+a("https://www.gabormelli.com/RKB/OntoNotes_Corpus") OntoNotes 5]
    |  corpus, the word vectors on #[+a("http://commoncrawl.org") Common Crawl].

+table(["Model", "spaCy", "Type", "UAS", "NER F", "POS", "WPS", "Size"])
    +row
        +cell #[+a("/models/en#en_core_web_sm") #[code en_core_web_sm]] 2.0.0a5
        each data in ["2.x", "neural"]
            +cell.u-text-right=data
        +cell.u-text-right 91.4
        +cell.u-text-right 85.5
        +cell.u-text-right 97.0
        +cell.u-text-right 8.2k
        +cell.u-text-right #[strong 36 MB]

    +row
        +cell #[+a("/models/en#en_core_web_lg") #[code en_core_web_lg]] 2.0.0a0
        each data in ["2.x", "neural"]
            +cell.u-text-right=data
        +cell.u-text-right #[strong 91.9]
        +cell.u-text-right #[strong 86.4]
        +cell.u-text-right #[strong 97.2]
        +cell.u-text-right #[em n/a]
        +cell.u-text-right 667 MB

    +row("divider")
        +cell #[code en_core_web_sm] 1.2.0
        each data in ["1.x", "linear", 86.6, 78.5, 96.6]
            +cell.u-text-right=data
        +cell.u-text-right #[strong 25.7k]
        +cell.u-text-right 50 MB

    +row
        +cell #[code en_core_web_md] 1.2.1
        each data in ["1.x", "linear", 90.6, 81.4, 96.7, "18.8k", "1 GB"]
            +cell.u-text-right=data