Meta Llama 3 Reviews & Product Details

Meta Llama 3 is pre-trained model with size of 8B to 70 B parameters which is useful to generate contents with more accuracy. What I like about this model is its performance which generate the content for given prompt and context in milliseconds. Also it is easy to use while using Python for AI use case development. Review collected by and hosted on G2.com.

While I did not oberve any downside while using this model in our use case, documentation for Meta Llama 3 says that testing done for this model does not cover all the scenarios. It will be great if model could be tested for all possible scenarios as it will make it more robust. Review collected by and hosted on G2.com.

Llama 3 has improved significantly over Llama 2 (Meta's previous generation LLM), and I have found it to be useful for multiple business use cases, such as Prompt Engineering, Agentic Workflows, Retrieval-Augmented Generation, and even for local Supervised Fine-tuning. The response quality, ability to follow instructions and even its ability to be tweaked to follow certain output formats is very good.

The best part is all the quality is free and open-source, so it can definitely serve as a good workhorse LLM while more complex requirements are reserved for OpenAI's GPT LLMs. Review collected by and hosted on G2.com.

Not as much of an improvement in terms of unique differentiability as I would have enjoyed - it's still fairly at the same level as Mistral Review collected by and hosted on G2.com.

Meta Llama 3 is fantastic at understanding and responding to natural language, making conversations feel smooth and natural. It's highly accurate than previous versions of Llama and gives relevant answers, which boosts productivity and user experience. It also intergrates with development applications. Plus, it's easy to customize for different uses because of the variations 7B,13B based on their personal projects or business needs. Review collected by and hosted on G2.com.

Meta Llama 3 can be quite complex and might be hard for beginners to use without a lot of training or good documentation. Sometimes, there are delays in responses, especially during busy times, which can be frustrating. Better customer support and an easier learning process would help new users a lot. Review collected by and hosted on G2.com.

I do love that they've incorporated it onto facebook to make it easy to edit posts. According to the ChatBot him/herself/themselves, Llama is designed with safety in mind, which means this bot is less likely to provide harmful or offensive responses (compared to other popular ones like chatgpt). I am not sure how accurate that is, but it didn't provide me with any harmful or offensive responses. Review collected by and hosted on G2.com.

It doesn't have plugins or a voice assistant like chatgpt does. Review collected by and hosted on G2.com.

I use it every day to supplement OpenAI and Anthropic models as a low cost alternative for narrow use cases. easy accessibility and strong position as an open-source competitor. performance is great, particularly on optimized platforms like Groq delivering blazing speeds. multimodal AI offers versatile alternative to main providers, broadening the scope of AI applications Review collected by and hosted on G2.com.

very steerable but takes work, quite wordy by default, not fully reinforced, fine tuning is not easy, absence of the larger 400B mode restricts its ability to fully replace OpenAI or Anthropic models. lack of native infrastructure support through Meta means ease of setup is dependent on other platforms Review collected by and hosted on G2.com.

I like that this AI large language model provides easy to digest answers. I frequnently use it to compose or refine email blasts. I also use Llama 3 for day to day business tasks such as unit of measure conversions and to gain industry specific knowledge on various products and services. Meta's customer support is wonderful as well which makes resolving any issues a breeze, almost 0 down time. On top of that it's an easy tool to intergate into any business since it came be accessed from a web brower. Overall implementing and using Lamma 3 is really easy and a win win all around. Review collected by and hosted on G2.com.

Somtimes it's a little slow to respond but that's probably due to this being an emerging technology. Review collected by and hosted on G2.com.

Llama 3 blew me away with how well it understands what I'm saying and gives helpful answers. It feels almost like chatting with a real person! It's also super flexible and can be used for all sorts of stuff, from writing emails to helping with creative tasks. I've even seen people use it for complex stuff like financial modeling! Plus, it's open-source, so you can customize it to your heart's content. I use this model everyday to simplify my daily tasks. Review collected by and hosted on G2.com.

Honestly, the only thing that bugs me most about Llama 3 is that it needs a pretty beefy computer to run smoothly. Not everyone's got access to that kind of superpower. And sometimes it spits out answers that are just plain wrong or too simple. Still, gotta say, the good stuff outweighs the bad, but those are definitely some things they could improve on. Review collected by and hosted on G2.com.

The best thing about Meta Llama 3 is its open source accesibility,

without any barriers that are usually found in proprietary systems.

Its performance, its efficiently fine-tuned.

Thereby its pretty good at reasoning and code generation along with multi-step problem-solving tasks. Review collected by and hosted on G2.com.

On a personal note one thing that I dislike about Meta Llama 3 and especially the 70B model is that it demands very high computational power.

Being an open source this can be a barrier to individual developer who dont have access to high end infrastructure. Review collected by and hosted on G2.com.

We can easily finetune on custom dataset and the instruction following capability is the best. This version of Llama is much better than the Llama 2 which needed some careful prompt engineering to get specific output. Many open-source libraries support integration of Llama weights as promp-tuner for training vision LLMs which works the best for dense image captioning tasks. Review collected by and hosted on G2.com.

Currently the lightweight version are not available and the model is bulky and more inference turnaround time for small NLP tasks. Review collected by and hosted on G2.com.

There are many things that I like abour LLama 3:

Variable model sizes:The model sizes range from 8B to 70B parameters, which provides flexibility in computational power and application. This enables to control costs based on the use

Performance: The model is exceptional in performing day to day tasks and can be used for many enterprise solutions (complex RAG) and agentic frameworks. It beats most of the open source models in benchmarks

Community support & integration: Llama 3 has a very good community support. It has integrations in all the AI frameworks like llamaindex and langchain

Ease of use and: Its easy to self host it on gpu vms with good documentation. It is also supported by various frameworks like vllm, ollama etc Review collected by and hosted on G2.com.

Code generation: The code generated by Llama 3 are not so great. There are lot of errors and usually fails in generating non python codes

Loss of context: Even though the context length is huge, it tends to loose context after 5k tokens even in larger models

Potential for Misuse: The open-source nature of Meta Llama 3, while democratizing AI technology, also opens doors for misuse. I have already seen some people training it to generate misinformation and other malicious activities Review collected by and hosted on G2.com.