Google Cloud Natural Language is a cloud-based Natural Language Processing API that proposes several advanced Natural Language Processing models. Despite being an important actor on the Natural Language Processing market, it is important to carefully review Google Natural Language's offer in order to understand if it the best solution for you. How does Google Natural Language Processing API compare to the NLP Cloud api in terms of pricing and features?
Google Natural Language consider that a request should contain less than 1,000 characters. If your request contains more than 1,000 characters, it is considered as several requests. For example, if you are trying to classify a piece of text made up of 3,500 characters, this is considered as 4 requests.
The price goes from $0,0005 to $0,002 per request depending on the feature you are using.
The first 5,000 requests are free every month, and if you use their text classification model, you get more free requests (30,000 per month).
The more requests you send, the more you're charged.
NLP Cloud adopts a totally different pricing strategy.
NLP Cloud's pricing is flat, which means that you have a number of requests included in your plan. If you want to change the number of requests, you can upgrade or downgrade your plan anytime. The interesting thing with such a pricing is that it is predictable: you always know in advance how much you will be charged at the end of the month.
NLP Cloud proposes several plans, depending on the number of requests you need, no matter the Natural Language Processing model you are going to use, and no matter the number of characters contained in your request. For example, 15 requests per minute cost $29 per month on CPU servers, and $99 per month on GPU servers. See the pricing page here.
Imagine that you want to classify pieces of text made up of 10,000 characters, at a rate of 15 requests per minute.
Google would consider that each request is actually equivalent to 10 requests (because each request can only be virtually made up of 1,000 characters). So at the end of the month you would perform 10 x 15 x 44,640 = 6,696,000 requests.
Taking into account their first 30k free requests, and their proportional pricing, you would eventually pay $3,140 per month.
For the same service you would pay $29 per month on NLP Cloud. The difference is quite impressive!
Google Natural Language is expensive and it is quite hard to predict how much you are going to be charged at the end of the month. Take time to do the math in advance in order to avoid surprises...
Google Natural Language develop their own in-house models, while NLP Cloud integrates the best open-source models available on the market. It's 2 different strategies, and both have pros and cons. Google have a perfect control on their models, but in return their models are black boxes: we don't know what is inside exactly.
Interesting feature: customers can fine-tune their own models on the Google Natural Language platform, and it is also the case on NLP Cloud. It is an interesting option if you think that the base models are not accurate enough and then should be tailored to your needs.
Also, Google have specific models dedicated to medical data analysis, that NLP Cloud don't have, so you might find it interesting if you're in the healthcare industry.
Now let's list all the proposed Natural Language Processing features.
Here are the Natural Language Processing features supported by Google Natural Language:
And here are the Natural Language Processing features supported by NLP Cloud as of this writing:
As you can see, more Natural Language Processing features are supported on NLP Cloud, and more should come soon.
Google Natural Language is a major actor in the Natural Language Processing market. They propose interesting features like the ability to train your own models, or address medical vocabulary.
However their API is very expensive. For the same price, you can get at least 100 times as many requests on the NLP Cloud API.
In terms of features, NLP Cloud propose many interesting Natural Language Processing models that Google don't propose, like text summarization, question answering, text generation, translation, language detection, tokenization, lemmatization...
Last of all, Google's pricing make it extremely hard to predict in advance how much you are going to be charged at the end of the month, which is not the case with NLP Cloud's flat pricing.
I hope this article helped you properly compare Google Natural Language and NLP Cloud! Feel free to try NLP Cloud here!
CTO at NLP Cloud