Elasticsearch: Ngram tokenizer perfomance

I try to search documents in elasticsearch with simple query like this:

{
    "query": {
        "match": { "name": "Test name" }
    }
}

and i have about 70 million documents in the index. I used whitespace tokenizer before, and it's works ok. But now i'm start using ngram, and even this queue runs for at least 6-7 seconds. I create index like this:

{
    "mappings": {
        "properties": {
            "name": {
                "type": "text",
                "analyzer": "custom_analyzer"
            }
        }
    },
    "settings": {
        "analysis": {
            "tokenizer": {
                "custom_tokenizer": {
                    "token_chars": [
                        "letter",
                        "digit",
                        "symbol",
                        "punctuation"
                    ],
                    "min_gram": "2",
                    "type": "ngram",
                    "max_gram": "3"
                }
            },
            "analyzer": {
                "custom_analyzer": {
                    "filter": [
                        "lowercase"
                    ],
                    "type": "custom",
                    "tokenizer": "custom_tokenizer"
                }
            }
        }
    }
}

Are there any ways to optimize the search? Or is ngram really that slow?