Model Selection Guide
Straico's Multi-Model Exploration and Selection
Model Comparison
We’ve curated the best closed and open-sourced models, and here we’ll guide you through the pros and cons of each. Discover how to select the perfect model to unlock the full potential of your AI experience
| Model Name | Word Limit per Chat | Coins per 100 Words | Moderation | Parameters | Training Data |
|---|---|---|---|---|---|
|
OpenAI: GPT-3.5 Turbo 16K |
~ 12.000 words |
0 coins |
Filtered |
13 Billion |
Up to Sep 2021 |
|
OpenAI: GPT-4 8K |
~ 6.000 words |
20 coins |
Filtered |
~ 1 Trillion |
Up to Sep 2021 |
|
OpenAI: GPT-4 Turbo 128K |
~ 96.000 words |
8 coins |
Filtered |
~ 1 Trillion |
Up to Apr 2023 |
|
Anthropic: Claude Instant v1 |
~ 75.000 words |
2 coins |
Filtered |
93 Billion |
Early 2023 |
|
Anthropic: Claude v2.1 |
~ 150.000 words |
12 coins |
Filtered |
137 Billion |
Mid 2023 |
|
Gryphe: MythoMax L2 |
~6.000 words |
1 coin |
Unfiltered |
13 Billion |
Early 2023 |
|
Google: PaLM 2 Bison |
~24.500 words |
1 coin |
Unfiltered |
340 Billion |
Mid 2021 |
|
Meta: Llama v2 70B Chat (beta) |
~3.000 words |
1 coin |
Unfiltered |
70 Billion |
Up to Sep 2022 |
|
Meta: CodeLlama 34B Instruct (beta) |
~3.000 words |
1 coin |
Unfiltered |
34 Billion |
Up to Sep 2022 |
|
Mistral 7B Instruct v0.1 (beta) |
~3.000 words |
1 coin |
Unfiltered |
7 Billion |
Mid 2021 |
|
Perplexity 70B Online |
~3.000 words |
1 coin |
Unfiltered |
70 Billion |
Real time internet access |
Word Limit Per Chat:
The maximum number of words the model can process in a single request. A higher word limit allows the model to take in more input words and generate more output words.
Coins per 100 words:
The coin cost for using 100 words of the selected model.
How the total words per interaction is calculated if no attachments are used:
Total words = Full current conversation + New message + Upcoming answer
How the total words per interaction is calculated if an attachment is used:
Total words = Attachment + Full current conversation + New message + Upcoming answer
Starting a new chat instead of continuing a conversation can significantly reduce the total words needed, as past context is reset. Another good option is using GPT 3.5 Turbo, which remains free regardless of word count on our platform.
Moderation:
Filtered models have built-in content guidelines to make appropriate moderation judgments. Unfiltered models do not have such measures, but this does not necessarily mean they will respond inappropriately.
Parameters:
Parameters are configurable variables internal to the language model. Their values are learned from training data. Parameters are key for the model to generate predictions and produce quality text output.
More parameters allow the model to handle more complex tasks, potentially improving overall output.
Training Data:
The cutoff date for data used to train the model. The model is knowledgeable of events and information that occurred before its training data date.