Open Router Models and its Strengths

Mixtral 8x7B

Ability to follow instructions
Complete requests
Generate creative text formats
Fine-tuned to be a helpful assistant
Sparse Mixture of Experts architecture contributes to high performance across different benchmarks

Dolphin 2.5 Mixtral 8x7B

Proficiency in coding
Uncensored nature
Reliable choice for tasks that require accurate and detailed language generation

Mistral-Medium

Proficiency in reasoning, code, JSON, and chat applications
Large context window
Closed-source, flagship status

Mistral-Small

Supports multiple languages including English, French, Italian, German, and Spanish
Coding capabilities
Versatile choice for multilingual and technical applications

Mistral-Tiny

Cost-effectiveness
Suitable for applications that require efficient and budget-friendly language processing solutions

Open Hermes 2.5

Creative and engaging writing
Some inconsistencies in instruction adherence and character consistency
Excels in real-time interactions
Proficiency in a variety of language tasks

Mistral 7B Instruct

Processing and generating responses based on specific instructions
Useful in tasks that require a high level of precision and adherence to guidelines

Psyfighter v2 13B

Ability to provide long, detailed responses
Improved prose and logic capabilities
Designed to offer high-quality outputs, especially in story mode
Valuable tool for various natural language processing tasks

Code Llama 34B Instruct

Generate text for code synthesis and understanding
Particularly useful in the context of Python

Phind Code Llama 34B

Designed for general code synthesis and understanding
Specifically for Python
An auto-regressive language model that uses an optimized architecture

Goliath 120B

Excels in roleplaying
Best LLM for this purpose
Outperforms smaller models in prose, understanding, and handling complex scenarios

PPLX 70B

Highly regarded for its translation capabilities
Cross-language understanding
Instruction following
Reading between the lines
Handling complex scenarios
Humor comprehension

PPLX 7B

Exceptional processing speed and efficiency
Generates answers within seconds
Produces an average of 140 tokens per second

Nous Hermes 70B

Provide long and detailed responses
Lower hallucination rates
Absence of OpenAI censorship mechanisms in its training data

Airoboros L 2 70B

Particularly adept at handling detailed coding tasks with specific criteria
Create applications based on detailed requirements
Write multi-threaded servers
Generate optimal responses to instructions utilizing a set of provided tools

Synthia 70B

Known for providing correct answers to a high percentage of multiple-choice questions
Ability to follow instructions and acknowledge all data input

Mythalion 13B

Available in various quantization methods
Each with different trade-offs between model size and quality

Yi 34B

Large bilingual (English/Chinese) language model
Contains 34 billion parameters
Trained on a dataset that supports a 4K sequence length
Can be expanded to 32K during inference

Yi 6B

Might excel in applications where quick and accurate language processing is required but with limited computational resources

Noromaid 20B

Performance in creating lewd stories and roleplay scenarios

Llama 2-70B Instruct v2

Performance has been compared to other LLMs, such as Llama2-70B
Achieves competitive results

Llama 2-13B

Strength lies in its ability to handle a high number of requests per second
Minimize latency
Provide cost-effective solutions for NLP tasks

Google Palm 2 & Google Palm 2 32k

Model architecture and objective have also been updated to achieve overall better performance
Faster inference
Fewer parameters to serve
Lower serving cost

Mistral Open Orca 7B

Performance has been compared to other LLMs, such as Llama2-70B
Achieves competitive results

Neural Chat 7B

Ability to conduct natural, flowing conversations
Suitable for chatbots and virtual assistant applications

MythoMist

Strength lies in its experimental nature
Active benchmarking process
Tailored to specific user goals

OpenChat

Fine-tuned with C-RLFT
Achieved the highest average performance among all 13B open models on three standard benchmarks

Zephyr 7B

Excels in performance and efficiency
Scores closely correlate with human ratings of model outputs
Outperforms larger models on benchmarks like MT-Bench and AlpacaEval

Nous Capybara 34B

Key strengths include fast performance
Suitable for real-time applications and large-scale language processing tasks

RWKV v.5

Ability to handle a wide range of languages
Performance comparable to transformer models
Efficient use of resources such as VRAM during both training and inference

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