Specialized Language Models
AI language model tailored specifically to your app
Knowledge Distillation
Knowledge Distillation
Knowledge Distillation
Distill knowledge from larger models to smaller, specialized models
Every time your app calls an LLM, we learn from its response and use it to train a smaller model. This specialized model is trained to perform like the LLM on your specific prompts while discarding unnecessary knowledge.
Every time your app calls an LLM, we learn from its response and use it to train a smaller model. This specialized model is trained to perform like the LLM on your specific prompts while discarding unnecessary knowledge.
Finance
Economics
Health
Food
Technology
Business
Marketing
Education
Environment
Sports
DIY (Do It Yourself)
Retail
Automotive
Tourism
Cryptocurrencies
Law
Personal Finance
Fitness
Gardening
Public Speaking
Photography
Culture
Fashion
Philosophy
Art
The knowledge you care about
Agriculture
Communication
Journalism
Medicine
Architecture
Parenting
History
Real Estate
Human Resources
Engineering
Astronomy
Home Improvement
Nutrition
Religion
Politics
Personal Development
Geography
Travel
Science
Psychology
Sociology
Literature
Music
Movies
Finance
Economics
Health
Food
Technology
Business
Marketing
Education
Environment
Sports
DIY (Do It Yourself)
Retail
Automotive
Tourism
Cryptocurrencies
Law
Personal Finance
Fitness
Gardening
Public Speaking
Photography
Culture
Fashion
Philosophy
Art
The knowledge you care about
Agriculture
Communication
Journalism
Medicine
Architecture
Parenting
History
Real Estate
Human Resources
Engineering
Astronomy
Home Improvement
Nutrition
Religion
Politics
Personal Development
Geography
Travel
Science
Psychology
Sociology
Literature
Music
Movies
Finance
Economics
Health
Food
Technology
Business
Marketing
Education
Environment
Sports
DIY (Do It Yourself)
Retail
Automotive
Tourism
Cryptocurrencies
Law
Personal Finance
Fitness
Gardening
Public Speaking
Photography
Culture
Fashion
Philosophy
Art
The knowledge you care about
Agriculture
Communication
Journalism
Medicine
Architecture
Parenting
History
Real Estate
Human Resources
Engineering
Astronomy
Home Improvement
Nutrition
Religion
Politics
Personal Development
Geography
Travel
Science
Psychology
Sociology
Literature
Music
Movies
Large Language Models
100s of Billions of Parameter
Specialized Language Models
1-10 Billion Parameter
Comparison
Comparison
Comparison
Know the difference
Large Language Model
$$$
$$$
$$$
$$$
Small Language Model
$
LLMs
SLMs
Large Language Models
Leading LLMs are trained to perform well across a variety of tasks—with training data spanning multiple disciplines, languages, and contexts. But ultimately, you don't care how well a model performs on the SAT or how well it knows poetry, history, and science in 80 languages—you need to solve specific problems in your app.
Large Language Model
$$$
$$$
$$$
$$$
Small Language Model
$
LLMs
SLMs
Large Language Models
Leading LLMs are trained to perform well across a variety of tasks—with training data spanning multiple disciplines, languages, and contexts. But ultimately, you don't care how well a model performs on the SAT or how well it knows poetry, history, and science in 80 languages—you need to solve specific problems in your app.
Large Language Model
$$$
$$$
$$$
$$$
Small Language Model
$
LLMs
SLMs
Large Language Models
Leading LLMs are trained to perform well across a variety of tasks—with training data spanning multiple disciplines, languages, and contexts. But ultimately, you don't care how well a model performs on the SAT or how well it knows poetry, history, and science in 80 languages—you need to solve specific problems in your app.
More Effective
More Effective
More Effective
Better
Cost
Performance
Accuracy
Better
Cost
Performance
Accuracy
Better
Cost
Performance
Accuracy
Model 13-B
Learning progress
Model 13-B
Learning progress
Model 13-B
Learning progress
Feedback
Feedback
Feedback
Train your own AI
By leveraging human feedback to train specialized models - you can correct some of the mistakes & hallucinations LLMs make, gaining better accuracy and better performance at the same time.
Cost of the model
Cost to parameters number chart
$$$
$$
$
0
0
1B
10B
100B
1000B
Parameters
you need
Cost of the model
Cost to parameters number chart
$$$
$$
$
0
0
1B
10B
100B
1000B
Parameters
you need
Cost of the model
Cost to parameters number chart
$$$
$$
$
0
0
1B
10B
100B
1000B
Parameters
you need
Optimization
Optimization
Optimization
Better performance, lower costs
Inference energy requirements, time and costs scale linearly with the size of the model. So when going from a 1 Trillion parameter model to a 1 Billion parameter model, you can expect significant improvements in cost and latency.
Models You Own
Models You Own
Models You Own
Datawizz trained models belong to you
Flexible solution
Download the weights and deploy our model wherever you like. This puts you in full control of your AI systems, freeing you from depending on large model providers and being subjected to their changes, outages and policies.
More Efficient
Smaller models are easier to deploy and can run efficiently on a variety of architecture and hardware platforms - freeing you from the tyranny of constrained GPU providers.
Multi-model Architecture
Multi-model Architecture
Multi-model Architecture
When it comes to AI - one size does not fit all
When building on a single large models, you end up with large generic models that can do a good job on average across a variety of use cases.
When building on a single large models, you end up with large generic models that can do a good job on average across a variety of use cases.
When building on a single large models, you end up with large generic models that can do a good job on average across a variety of use cases.
Your App
Analysis
Language
Context Size
Task
Summarization
Extraction
English
French
Small
Large
Model A
Model B
Model C
Model D
Model E
Your App
Analysis
Language
Context Size
Task
Summarization
Extraction
English
French
Small
Large
Model A
Model B
Model C
Model D
Model E
Your App
Analysis
Language
Context Size
Task
Summarization
Extraction
English
French
Small
Large
Model A
Model B
Model C
Model D
Model E
Deploy multiple models
Datawizz lets you deploy multiple models and dynamically route requests to them, leveraging highly specialized, mission specific models.
Hyper-specialization
Hyper-specialization allows your models to be more accurate at specific tasks, and enables you to leverage smaller and more efficient model architectures.
Seamless Integration
Seamless Integration
Seamless Integration
Instantly Train on Your Data
Datawizz model training is deeply integrated with our AI data management platform - meaning every log you collect can instantly be used for model training and experimentation.
Your data is constantly managed
in a training-ready format.
With Datawizz you can forget about:
Data collection
Data cleansing
Data preparation
Choose the Right Base Model
Choose the Right Base Model
Choose the Right Base Model
Datawizz Offers a Variety of Base Models to Fit Your Specific Task
We include a set of pre trained models suited for general language tasks, coding tasks, various languages, and unique use cases like longer contexts or structured outputs. Combined with the Datawizz evaluation platform, you can easily find the right architecture for your workloads.
We include a set of pre trained models suited for general language tasks, coding tasks, various languages, and unique use cases like longer contexts or structured outputs. Combined with the Datawizz evaluation platform, you can easily find the right architecture for your workloads.
We include a set of pre trained models suited for general language tasks, coding tasks, various languages, and unique use cases like longer contexts or structured outputs. Combined with the Datawizz evaluation platform, you can easily find the right architecture for your workloads.
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Llama 3.2 1B
7B Parameters
Description
Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Best Suited For
Simple language tasks, classification, extraction
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Llama 3.2 1B
7B Parameters
Description
Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Best Suited For
Simple language tasks, classification, extraction
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Llama 3.2 1B
7B Parameters
Description
Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Best Suited For
Simple language tasks, classification, extraction
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Llama 3.2 1B
7B Parameters
Description
Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Best Suited For
Simple language tasks, classification, extraction
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Llama 3.2 1B
7B Parameters
Description
Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Best Suited For
Simple language tasks, classification, extraction
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Llama 3.2 1B
7B Parameters
Description
Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Best Suited For
Simple language tasks, classification, extraction
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Llama 3.2 1B
7B Parameters
Description
Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Best Suited For
Simple language tasks, classification, extraction
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Llama 3.2 1B
7B Parameters
Description
Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Best Suited For
Simple language tasks, classification, extraction
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Llama 3.2 1B
7B Parameters
Description
Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Best Suited For
Simple language tasks, classification, extraction
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Llama 3.2 1B
7B Parameters
Description
Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Best Suited For
Simple language tasks, classification, extraction
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Llama 3.2 1B
7B Parameters
Description
Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Best Suited For
Simple language tasks, classification, extraction
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Llama 3.2 1B
7B Parameters
Description
Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Best Suited For
Simple language tasks, classification, extraction
Phi-3 Mini
3.8B Parameters
Description
Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length.
Best Suited For
Content generation, text summarization
Cohere Command-R 7B
7B Parameters
Description
C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code.
Best Suited For
Extraction and reasoningon large context windows
Evaluate and Select
Evaluate and Select
Evaluate and Select
Choose the right model for your needs
Datawizz offers advanced model evaluation and comparison tools, giving you a deeper understanding of how different models perform for your tasks.
Datawizz offers advanced model evaluation and comparison tools, giving you a deeper understanding of how different models perform for your tasks.
Datawizz offers advanced model evaluation and comparison tools, giving you a deeper understanding of how different models perform for your tasks.
You:
Create a short tagline for a new cybersecurity software for businesses
gpt-4o:
Protect what matters with advanced cybersecurity
llama-3.2-1B:
Fortify your business with unbeatable cyber defense.
You:
I like the GPT's answer better
Your prompt...
You:
Create a short tagline for a new cybersecurity software for businesses
gpt-4o:
Protect what matters with advanced cybersecurity
llama-3.2-1B:
Fortify your business with unbeatable cyber defense.
You:
I like the GPT's answer better
Your prompt...
You:
Create a short tagline for a new cybersecurity software for businesses
gpt-4o:
Protect what matters with advanced cybersecurity
llama-3.2-1B:
Fortify your business with unbeatable cyber defense.
You:
I like the GPT's answer better
Your prompt...
Real Data
Easily set up evaluations based on your existing data & human feedback to test-drive models with real world data.
Multi-Method
Choose from a variety of evaluation functions, including Rogue scores, LLM as judge vector similarity to evaluate models for any task.
Fire and Forget
Evaluations are easy to configure and seamless to run - no Jupyter notebooks required.
Eco Friendly
Smaller Models - Smaller Footprint
Large language models are power hungry - taxing our grids and raising CO2 emissions. By choosing smaller, specialize models - you choose the energy efficient, environmentally friends path.
100x
Smaller models can use up to 100x less energy for the same task than larger models - significantly cutting back energy consumption, pollution, greenhouse gas emissions.