travel lab tech reddit

• Toll Free (800) 811-0064
• Long-Term Care
• Cardiopulmonary
• Staffing Solutions
• Corporate Careers
• Internship Program
• Growth & Development
• Community Involvement
• Leadership Team
• Quick Apply

Travel as a Medical Lab Technician

Browse Travel Med Lab Tech Jobs with LRS Healthcare.

Traveling as a Med Lab Tech with LRS Healthcare

At LRS Healthcare, our expert recruiters act as your personal career coach to ensure you are placed on only the best MLT travel jobs based on your professional and personal preferences.

Travel healthcare workers experience job flexibility and opportunities perm jobs simply can’t provide. Healthcare facilities nationwide need quality MLT professionals, like you. Travel med lab tech jobs give you the freedom to make choices that are best for you.

What to expect

Applying for medical lab tech travel jobs.

The first step in your healthcare travel career is to browse MLT travel jobs with LRS Healthcare and apply . Next, a recruiter will reach out to help you finalize your application and traveler profile, share job details (like pay and start dates) and work to get you the healthcare travel assignment of your dreams!

Download the Complete Checklist for Every New Healthcare Travel Assignment

of Traveling as a  Medical Lab Technician

Working as a healthcare traveler gives you the freedom to take control of your career by choosing the job, location, and facility you desire. Our recruiters work on your behalf so you can make great money and enjoy the traveler lifestyle you dream about.

Additional perks include:

Excellent Weekly Pay

Explore New Cities

Fun and Flexible Lifestyle

On-the-Job Experiences

Professional Growth

Extended Time Off Between Assignments

Meet New People

24-Hour Support

With all of this change and excitement, it may take some time to get comfortable in your new job and location. Don’t worry this is expected and your recruiter will be there at every step of your journey! Learn more about travel opportunities for Laboratory Professionals.

Asked Questions

01. Healthcare traveler requirements vary by facility and state. As a best practice, be sure your licenses and certifications are up to date before you apply . You may need to obtain an additional license specific to the state in which you plan to work. Med Lab Techs with at least 2 years of on-the-job experience have better odds of getting placed in premium assignments.

02. It’s important to first find and commit to a healthcare staffing agency you want to work with, then just go for it – apply for the job! LRS Healthcare recruiters take pride in listening to your requests and finding you the best travel job that pays well and matches your lifestyle and interests.

03. Pay packages vary by experience, job, facility, and agency. Sites and job boards that promote weekly pay either display the pay before or after taxes and include or exclude travel and housing stipends. These variables affect what your take home pay could be and could potentially vary from the number promoted on the job post. For an accurate pay package breakdown, we recommend you speak with an LRS Healthcare recruiter so we can review your personalized pay package with you in full transparency and answer your questions so you know what to expect on each pay stub.

04. A standard MLT travel assignment is 13 weeks. This time frame gives you an opportunity to learn the job, explore the city, and make new friends. No matter the length of your allied healthcare travel assignment, if you’ve found a job (or city) you enjoy, you can always request an extension .

24/7/365 Benefits

Beyond-your-basic benefits.

Licensure Reimbursement

Certification Reimbursement

Traveler Experience Team

Referral Bonus

LifeWorks EAP

Clinical Team

Learn more about our benefits .

From the LRS Healthcare Blog

2024 conferences for healthcare travelers, pros & cons of being a traveling medical lab tech, upgrade your career from ota to ot: what to know (and do).

Why Choose LRS Healthcare?

Your success is our priority. That’s why we make the traveler experience easy, so you can spend more time living your life and caring for your patients. Here are just a few more reasons to travel with us.

Traveler First:

You’re never just a number to us. We take the time to learn about you, including your career goals and desired destinations. Your recruiter will guide you from one assignment to the next and be your advocate throughout your journey with us.

Responsive:

Submit your online application, and we’ll be in touch right away. Once we’ve gotten to know you and matched you to an ideal position, we’ll work together to collect the rest of the details.

Full Service:

Along with your recruiter, you’ll have access to our dedicated operations and traveler experience teams. They help take care of all the details to make your assignment the very best it can be. You won’t go it alone—you can contact us any time, 24/7/365.

Travel with LRS Healthcare

Ready to hit the road for your next assignment.

• Quick Profile
• Traveler FAQs

How to Become a Travel Medical Laboratory Tech

A medical laboratory tech performs complex tests to help other professionals in the healthcare industry like doctors and nurse practitioners, diagnose and treat diseases such as diabetes and cancer. They may specialize in various areas like immunology, molecular biology, microbiology, hematology, cytotechnology and clinical chemistry. This role also enjoys the flexibility of having the opportunity to work as a permanent staff member or as a travel medical lab technologist at facilities across the country.

Just like a travel therapist, a travel MLT can earn more money while enjoying outstanding benefits like free housing or a housing stipend, along with opportunities for career advancement, the chance to experience new destinations and meet new people.

What Is a Travel Medical Lab Tech?

A travel medical lab tech is generally tasked with the same responsibilities as an MLT who works directly for a facility. That can entail setting up and sanitizing a laboratory, matching blood compatibility for transfusions, preparing specimens, collecting blood samples, analyzing fluid chemical content and more. Instead of being a permanent staff member, the travel medical lab tech works with a recruiter at a healthcare travel company. The recruiter then helps to set them up on assignments in various locations around the country, usually for 13 weeks at a time.

Access unadvertised travel MLT jobs

The Benefits of Being a Travel Medical Laboratory Technician

The benefits of being a medical lab tech not only include earning a good salary, but the potential to make a difference in patients’ lives. Testing blood and other samples to help the physician diagnose what is wrong, can and often does lead to lives being saved. Being a travel MLT brings even more benefits like a higher salary, getting paid to travel, living in new places, learning new skills, getting free private housing and more.

How Much Does a Travel Medical Lab Tech Make?

The salary for a travel medical lab tech varies depending on location, just like any other job. The average salary across the country for an MLT working in a permanent position is $51,505, whereas the average travel MLT makes an average of nearly $68,000 per year. The highest paying states for travel medical lab techs are California, with the average salary at $80,500, followed by Rhode Island, Alaska, Connecticut and Massachusetts. The lowest paying states pay salaries that range from just over $50,000 to $54,000 annually and include Alabama, New Mexico, South Carolina, Louisiana and Arkansas.

Learn about travel MLT jobs

Can New Grad MLTs Become Traveling Medical Lab Techs?

Due to the demand for medical laboratory technicians, though rare,  it is possible to become a travel MLT as a new grad. Travel Medical lab Techs are most often required to have a minimum of year of experience.  Two years of experience is ideal. Healthcare travel companies have knowledgeable recruiters on staff who are willing to advise you on how to make the most out of the education and laboratory experience you have, helping you to enter the exciting world of healthcare travel. The most important thing is to be as flexible as possible and to be willing to take an assignment where the need is greatest.

How Does a Medical Laboratory Tech Find Travel Jobs?

While you’re likely to find plenty of job openings simply by doing a Google search, just like travel therapy and other healthcare travel jobs, most can be found by signing up with a travel healthcare staffing agency. As there is such a long list of these companies, you’ll need to determine which have assignments for MLTs that meet your particular requirements. As you can imagine, that can be quite time consuming.

The simplest approach to finding a MLT travel job and getting matched with travel staffing companies that can meet your needs and interests is to use our free service for Medical Lab Techs. By submitting a brief online form , we’ll match your preferences with the industry leading travel staffing companies. You’ll no longer worry about jobs being outdated as you’ll gain access to unadvertised travel jobs and you’ll save time on researching companies. Start here!

Are There In-House Housing Specialists Available to Assist Travelers with Arrangements?

Our travel partners have in-house housing and travel specialists available to assist medical laboratory travelers with their arrangements.

Are There Professionals specializing in Medical Laboratory Professionals at AlliedTravelWeb.com?

At AlliedTravelWeb.com, we take pride in our expertise in making medical staffing connections. We have a dedicated team of professionals who specialize in matching healthcare professionals with the perfect job opportunities in the medical laboratory field. Whether you are seeking a travel job or a permanent position, our partners offer a wide range of medical employment opportunities at top-notch facilities nationwide. Our partners are experienced and knowledgeable in the specific needs and requirements of Medical Laboratory professionals. They will provide you with the necessary support and guidance throughout every step of the process, ensuring that we find the ideal travel healthcare job for you.

Everything You Need to Know About Guaranteed Hours on Your Healthcare Travel Assignment

Weekly Roundup: HOT Therapy Travel Jobs, HOT Allied Travel Jobs

How to Become a Cath Lab Traveler

What is a Cath Lab?

Let’s start by addressing what exactly Cath Lab means. Cardiac Catheterization Laboratory, or Cath Lab for short, is a healthcare area where doctors and other healthcare professionals perform minimally invasive tests and advanced cardiac procedures to diagnose and treat cardiovascular disease.

A cardiac catheterization procedure involves threading a long, thin tube, called a catheter, through an artery or vein in the leg or arm and into the heart. Cardiac catheterization can be performed due to emergencies like a heart attack.  Other times, a cardiac catheterization (also known as an angiogram) is performed as a diagnostic tool to check for blockages for suspected coronary artery diseases.

What does a Cath Lab nurse do?

Cath Lab nurses work with doctors to provide patients with cardiac care before, during, and after operations. First, they’ll examine patients to ensure they are in good condition for the procedure. During the process, they monitor patients’ vitals. Lastly, following surgery, Cath Lab nurses assist patients through recovery. They may also provide care expertise after the patient has fully recovered.

Duties of a Cath Lab professional Handling paperwork such as consent forms and filing documents with patient records. Preparing for operations, like sterilizing the space and shaving the patient at the catheter insertion site. Monitoring patient vitals and sedation during and after operations. Sharing discharge paperwork and care instructions with patients and/or family members. Revising patient charts.

What’s the difference between a Cath Lab RN and a Cath Lab Tech?

Although Cath Lab nurses and technicians work together during every cardiac catheterization, there are differences in their roles. Nurses handle more of the direct patient care, while the technician is responsible for more of the processes and equipment used in the surgery. They also do not provide medication to patients as an RN does.

Education and Required Skills

Education and certification requirements vary by hospital, but most facilities require an associate’s degree (ADN) or a bachelor’s degree in nursing (BSN). Upon degree completion, candidates must pass the National Council Licensure Examination (NCLEX-RN) exam from the National Council of State Boards of Nursing (NCSBN). Once they pass, nurses can officially become registered nurses (RN) in their state. Depending on the location, cath lab nurses might need to complete specific continuing education units to maintain their licensure.

Obtaining the Registered Cardiovascular Invasive Specialist credential can help a cath lab technician qualify for more opportunities, especially in a competitive market. To sit for the RCIS exam, candidates must meet the minimum education requirements established by Cardiovascular Credentialing International and submit additional supporting documentation, including:

• Educational transcripts
• Clinical verification letters
• Employment verification letters

Basic Life Support (BLS) and Advanced Cardiac Life Support (ACLS) are also beneficial certifications.

Besides having the proper education and certifications, Cath Lab professionals should have the following:

• Attention to detail
• Strong organizational skills
• Strong communication skills
• Physical endurance
• Mental and emotional resilience

Where do Cath Lab travelers work?

The U.S. Bureau of Labor Statistics (BLS) also reports that the demand for Cath Lab nurses will increase by 7% from 2019 to 2029, meaning they have abundant opportunities in many places.  However, according to Indeed , the top cities for Cath Lab professionals are:

• Los Angeles, CA
• Chicago, IL
• Atlanta, GA
• Columbia, MO
• Phoenix, AZ

Benefits and things to consider

The national average salary for Cath Lab nurses is $121,364 per year, depending on experience. That’s a big check in the pro column. However, working in this area is a physically taxing position as well as an emotional one. When becoming a traveler, these are big things to consider since healthcare travelers are expected to hit the ground running and adapt quickly to new facilities and teams.

How Magnet can help

Does a healthcare traveling career in Cardiac Catheterization send your heart into a flutter? Magnet is here to ensure the staffing process goes smoothly so you can focus on providing exceptional care. We provide 24/7/365 service to our travelers to guarantee your needs are met.

Contact a recruiter today, and let’s get you on your way toward professional and personal excellence.

You May also like…

Balancing Work and Family Life as a Healthcare Traveler: Tips for Traveling with Your Loved Ones

Jun 29, 2023

. Healthcare traveler families often face unique obstacles, such as finding suitable housing, ensuring access to quality education, and maintaining strong relationships with loved ones while being away for extended periods. Below, we’ll offer tips and advice on navigating these challenges and provide insight into what it takes to balance a career in healthcare travel with family life successfully.

Find Freedom and Fulfillment as a Certified Nursing Assistant Traveler: 4 Ways Travel Nursing Can Take Your Career to New Heights

Jun 12, 2023

Getting started as a traveling CNA brings all the rewards. But you could be wondering – where do I start? At Magnet, our team of experienced recruiters work with you to learn about your goals and aspirations to find a travel assignment that is what you are look for!

What to Know as a New Healthcare Traveler: Magnet Medical FAQs Answered

May 23, 2023

Becoming a healthcare traveler is a complex process. Have questions? Magnet Medical has answers.

Travel cardiac cath lab tech career guide

Table of Contents

Travel cardiac cath lab techs, also known as cardiac catheterization lab technologists, are diagnostic imaging specialists who assist physicians with minimally-invasive procedures in cardiac cath labs. Travel cardiac cath lab techs use imaging to help visualize cardiac tissue and vasculature so doctors can perform procedures such as biopsies, stenting, balloon angioplasties, and more. The job outlook for travel cardiac cath lab technologists is bright, with demand expected to remain strong due to an aging population and the widespread prevalence of cardiovascular issues in patients such as coronary artery disease, hypertension, and heart failure. The skills that travel cardiac cath lab techs have make them a valuable asset to interventional cardiac teams.

At Nomad Health, we understand that travel cardiac cath lab tech jobs can be demanding, but incredibly rewarding too. That’s why we’re dedicated to removing obstacles for our travel cardiac cath lab techs, so they can thrive personally and professionally wherever they are. If you’re starting your travel journey, or want to learn more about what it’s like to be a travel cardiac cath lab tech, our guide is here to help.

What does a travel cardiac cath lab tech do?

Travel cardiac cath lab techs play an essential role in diagnosing and treating patients with cardiovascular conditions. They are tasked with assisting physicians during cardiac procedures in cardiac cath labs by passing instruments, injecting contrast agents, operating fluoroscopy equipment, capturing live images, and attending to other crucial needs. Travel cardiac cath lab techs have a strong understanding of catheterization procedures and know how to collaborate and communicate with other medical professionals, patients, and their families. Additionally, travel cardiac cath lab techs have routine tasks they must complete throughout the day, including:

Cath lab setup

Travel cardiac cath lab techs are responsible for making sure the catheterization lab is clean, stocked with appropriate supplies, and ready for scheduled procedures.

Patient prep

Travel cardiac cath lab techs will help patients get settled in and prepared for their procedure. They will answer patients questions and assist the patient so they are in the correct positioning on the table. They will also apply electrodes for any EKG monitors being used.

Assist with procedures

One of the most important tasks of a travel cardiac cath lab tech is to safely assist the medical team with cardiac procedures. During procedures in the cath lab, these techs are responsible for operating fluoroscopy equipment (depending on state regulations), monitoring patient vital signs, maintaining sterile procedure, and assisting the physician by passing them instruments and anticipating their needs. They also ensure that the patient and team is shielded from excessive radiation.

Post-procedure

After each procedure, the travel cardiac cath lab tech will transfer the patient into the recovery area. They will also sterilize all the instruments used during the procedure and update the patient's medical records to include any observations noted during the procedure.

Closing checks

At the end of the day, travel cardiac cath lab techs will ensure the lab is cleaned, sterilized, and supplies have been restocked for the next day. They will also check all equipment in the cath lab and report any issues to the maintenance team.

How much does a travel cardiac cath lab tech earn?

The total compensation of travel cardiac cath lab techs depends on many different factors including location, experience, facility demand, education, and certifications. Travel cardiac cath lab techs at Nomad Health earn a total weekly compensation of $72 per hour, including a travel stipend.

How do you become a licensed travel cardiac cath lab tech?

The journey to become a travel cardiac cath lab tech takes about three to four years total, although everyone’s career trajectory is slightly different. Take a look at the steps below:

Step 1: complete educational requirements

The first step to becoming a travel cardiac cath lab tech is to earn at least an associate’s degree in cardiovascular technology, or radiologic technology. Here, you’ll get classroom education accompanied by hands-on clinical training.

Step 2: pass the certification exam

After graduation, you can sit for a certification exam through the Cardiovascular Credentialing International (CCI) or the American Registry of Radiologic Technologists (ARRT).

Step 3: fulfill state licensing requirements

Keep in mind that as a travel cardiac cath lab tech, you'll need to follow each state's licensing requirements. Some state’s may require certification from the CCI versus the ARRT. Be sure to check with each state’s regulatory board to know exactly what you need.

What certification do travel cardiac cath lab techs need?

Certifications are an excellent way for travel cardiac cath lab techs to show their expertise and increase their skills. Most of these certifications are awarded by the American Registry of Radiologic Technologists (ARRT) or the Cardiovascular Credentialing International (CCI). There are a few certifications that are frequently required to work as a travel cardiac cath lab technologist:

Registered Cardiovascular Invasive Specialist (RCIS)

This key certification is awarded by Cardiovascular Credentialing International (CCI) and is designed for rad techs who want to work in the cath lab. Some facilities accept this certification.

Some facilities will consider this this certification, along with previous cardiac cath lab tech experience, as sufficient qualification for a job.

Travel cardiac cath lab techs can earn this certification to pursue a specialization in cardiac-interventional radiology. Some facilities and states may require this certification.

Advanced Cardiac Life Support (ACLS)

If working with adult patients, ACLS is required for travel cardiac cath lab techs. The need for patients with advanced life support is higher in this population.

Pediatric Advanced Life Support (PALS)

For those working with pediatric patients, PALS will be required; the need for advanced life support is higher in this population.

Basic Life Support (BLS) Certification

All hospitals and facilities require travel cardiac cath lab techs to be certified in basic life support in the event of an emergency situation.

Travel cardiac cath lab tech sources

• American Registry of Radiologic Technologists (ARRT). (n.d.). Cardiac Interventional Radiography. Retrieved from https://www.arrt.org/pages/earn-arrt-credentials/credential-options/cardiac-interventional-radiography
• Cardiovascular Credentialing International (CCI). (n.d.). Registered Cardiovascular Invasive Specialist (RCIS). Retrieved from https://cci-online.org/credentials/registered-cardiovascular-invasive-specialist/

I am with Nomad and LOVE them...they really love feedback and are open to hearing what nurses need and want. Terri N. ICU RN

Find the best travel jobs

Author profile.

Our approach

• Responsibility
• Infrastructure
• Try Meta AI

RECOMMENDED READS

• 5 Steps to Getting Started with Llama 2
• The Llama Ecosystem: Past, Present, and Future
• Introducing Code Llama, a state-of-the-art large language model for coding
• Meta and Microsoft Introduce the Next Generation of Llama
• Today, we’re introducing Meta Llama 3, the next generation of our state-of-the-art open source large language model.
• Llama 3 models will soon be available on AWS, Databricks, Google Cloud, Hugging Face, Kaggle, IBM WatsonX, Microsoft Azure, NVIDIA NIM, and Snowflake, and with support from hardware platforms offered by AMD, AWS, Dell, Intel, NVIDIA, and Qualcomm.
• We’re dedicated to developing Llama 3 in a responsible way, and we’re offering various resources to help others use it responsibly as well. This includes introducing new trust and safety tools with Llama Guard 2, Code Shield, and CyberSec Eval 2.
• In the coming months, we expect to introduce new capabilities, longer context windows, additional model sizes, and enhanced performance, and we’ll share the Llama 3 research paper.
• Meta AI, built with Llama 3 technology, is now one of the world’s leading AI assistants that can boost your intelligence and lighten your load—helping you learn, get things done, create content, and connect to make the most out of every moment. You can try Meta AI here .

Today, we’re excited to share the first two models of the next generation of Llama, Meta Llama 3, available for broad use. This release features pretrained and instruction-fine-tuned language models with 8B and 70B parameters that can support a broad range of use cases. This next generation of Llama demonstrates state-of-the-art performance on a wide range of industry benchmarks and offers new capabilities, including improved reasoning. We believe these are the best open source models of their class, period. In support of our longstanding open approach, we’re putting Llama 3 in the hands of the community. We want to kickstart the next wave of innovation in AI across the stack—from applications to developer tools to evals to inference optimizations and more. We can’t wait to see what you build and look forward to your feedback.

Our goals for Llama 3

With Llama 3, we set out to build the best open models that are on par with the best proprietary models available today. We wanted to address developer feedback to increase the overall helpfulness of Llama 3 and are doing so while continuing to play a leading role on responsible use and deployment of LLMs. We are embracing the open source ethos of releasing early and often to enable the community to get access to these models while they are still in development. The text-based models we are releasing today are the first in the Llama 3 collection of models. Our goal in the near future is to make Llama 3 multilingual and multimodal, have longer context, and continue to improve overall performance across core LLM capabilities such as reasoning and coding.

State-of-the-art performance

Our new 8B and 70B parameter Llama 3 models are a major leap over Llama 2 and establish a new state-of-the-art for LLM models at those scales. Thanks to improvements in pretraining and post-training, our pretrained and instruction-fine-tuned models are the best models existing today at the 8B and 70B parameter scale. Improvements in our post-training procedures substantially reduced false refusal rates, improved alignment, and increased diversity in model responses. We also saw greatly improved capabilities like reasoning, code generation, and instruction following making Llama 3 more steerable.

*Please see evaluation details for setting and parameters with which these evaluations are calculated.

In the development of Llama 3, we looked at model performance on standard benchmarks and also sought to optimize for performance for real-world scenarios. To this end, we developed a new high-quality human evaluation set. This evaluation set contains 1,800 prompts that cover 12 key use cases: asking for advice, brainstorming, classification, closed question answering, coding, creative writing, extraction, inhabiting a character/persona, open question answering, reasoning, rewriting, and summarization. To prevent accidental overfitting of our models on this evaluation set, even our own modeling teams do not have access to it. The chart below shows aggregated results of our human evaluations across of these categories and prompts against Claude Sonnet, Mistral Medium, and GPT-3.5.

Preference rankings by human annotators based on this evaluation set highlight the strong performance of our 70B instruction-following model compared to competing models of comparable size in real-world scenarios.

Our pretrained model also establishes a new state-of-the-art for LLM models at those scales.

To develop a great language model, we believe it’s important to innovate, scale, and optimize for simplicity. We adopted this design philosophy throughout the Llama 3 project with a focus on four key ingredients: the model architecture, the pretraining data, scaling up pretraining, and instruction fine-tuning.

Model architecture

In line with our design philosophy, we opted for a relatively standard decoder-only transformer architecture in Llama 3. Compared to Llama 2, we made several key improvements. Llama 3 uses a tokenizer with a vocabulary of 128K tokens that encodes language much more efficiently, which leads to substantially improved model performance. To improve the inference efficiency of Llama 3 models, we’ve adopted grouped query attention (GQA) across both the 8B and 70B sizes. We trained the models on sequences of 8,192 tokens, using a mask to ensure self-attention does not cross document boundaries.

Training data

To train the best language model, the curation of a large, high-quality training dataset is paramount. In line with our design principles, we invested heavily in pretraining data. Llama 3 is pretrained on over 15T tokens that were all collected from publicly available sources. Our training dataset is seven times larger than that used for Llama 2, and it includes four times more code. To prepare for upcoming multilingual use cases, over 5% of the Llama 3 pretraining dataset consists of high-quality non-English data that covers over 30 languages. However, we do not expect the same level of performance in these languages as in English.

To ensure Llama 3 is trained on data of the highest quality, we developed a series of data-filtering pipelines. These pipelines include using heuristic filters, NSFW filters, semantic deduplication approaches, and text classifiers to predict data quality. We found that previous generations of Llama are surprisingly good at identifying high-quality data, hence we used Llama 2 to generate the training data for the text-quality classifiers that are powering Llama 3.

We also performed extensive experiments to evaluate the best ways of mixing data from different sources in our final pretraining dataset. These experiments enabled us to select a data mix that ensures that Llama 3 performs well across use cases including trivia questions, STEM, coding, historical knowledge, etc.

Scaling up pretraining

To effectively leverage our pretraining data in Llama 3 models, we put substantial effort into scaling up pretraining. Specifically, we have developed a series of detailed scaling laws for downstream benchmark evaluations. These scaling laws enable us to select an optimal data mix and to make informed decisions on how to best use our training compute. Importantly, scaling laws allow us to predict the performance of our largest models on key tasks (for example, code generation as evaluated on the HumanEval benchmark—see above) before we actually train the models. This helps us ensure strong performance of our final models across a variety of use cases and capabilities.

We made several new observations on scaling behavior during the development of Llama 3. For example, while the Chinchilla-optimal amount of training compute for an 8B parameter model corresponds to ~200B tokens, we found that model performance continues to improve even after the model is trained on two orders of magnitude more data. Both our 8B and 70B parameter models continued to improve log-linearly after we trained them on up to 15T tokens. Larger models can match the performance of these smaller models with less training compute, but smaller models are generally preferred because they are much more efficient during inference.

To train our largest Llama 3 models, we combined three types of parallelization: data parallelization, model parallelization, and pipeline parallelization. Our most efficient implementation achieves a compute utilization of over 400 TFLOPS per GPU when trained on 16K GPUs simultaneously. We performed training runs on two custom-built 24K GPU clusters . To maximize GPU uptime, we developed an advanced new training stack that automates error detection, handling, and maintenance. We also greatly improved our hardware reliability and detection mechanisms for silent data corruption, and we developed new scalable storage systems that reduce overheads of checkpointing and rollback. Those improvements resulted in an overall effective training time of more than 95%. Combined, these improvements increased the efficiency of Llama 3 training by ~three times compared to Llama 2.

Instruction fine-tuning

To fully unlock the potential of our pretrained models in chat use cases, we innovated on our approach to instruction-tuning as well. Our approach to post-training is a combination of supervised fine-tuning (SFT), rejection sampling, proximal policy optimization (PPO), and direct preference optimization (DPO). The quality of the prompts that are used in SFT and the preference rankings that are used in PPO and DPO has an outsized influence on the performance of aligned models. Some of our biggest improvements in model quality came from carefully curating this data and performing multiple rounds of quality assurance on annotations provided by human annotators.

Learning from preference rankings via PPO and DPO also greatly improved the performance of Llama 3 on reasoning and coding tasks. We found that if you ask a model a reasoning question that it struggles to answer, the model will sometimes produce the right reasoning trace: The model knows how to produce the right answer, but it does not know how to select it. Training on preference rankings enables the model to learn how to select it.

Building with Llama 3

Our vision is to enable developers to customize Llama 3 to support relevant use cases and to make it easier to adopt best practices and improve the open ecosystem. With this release, we’re providing new trust and safety tools including updated components with both Llama Guard 2 and Cybersec Eval 2, and the introduction of Code Shield—an inference time guardrail for filtering insecure code produced by LLMs.

We’ve also co-developed Llama 3 with torchtune , the new PyTorch-native library for easily authoring, fine-tuning, and experimenting with LLMs. torchtune provides memory efficient and hackable training recipes written entirely in PyTorch. The library is integrated with popular platforms such as Hugging Face, Weights & Biases, and EleutherAI and even supports Executorch for enabling efficient inference to be run on a wide variety of mobile and edge devices. For everything from prompt engineering to using Llama 3 with LangChain we have a comprehensive getting started guide and takes you from downloading Llama 3 all the way to deployment at scale within your generative AI application.

A system-level approach to responsibility

We have designed Llama 3 models to be maximally helpful while ensuring an industry leading approach to responsibly deploying them. To achieve this, we have adopted a new, system-level approach to the responsible development and deployment of Llama. We envision Llama models as part of a broader system that puts the developer in the driver’s seat. Llama models will serve as a foundational piece of a system that developers design with their unique end goals in mind.

Instruction fine-tuning also plays a major role in ensuring the safety of our models. Our instruction-fine-tuned models have been red-teamed (tested) for safety through internal and external efforts. ​​Our red teaming approach leverages human experts and automation methods to generate adversarial prompts that try to elicit problematic responses. For instance, we apply comprehensive testing to assess risks of misuse related to Chemical, Biological, Cyber Security, and other risk areas. All of these efforts are iterative and used to inform safety fine-tuning of the models being released. You can read more about our efforts in the model card .

Llama Guard models are meant to be a foundation for prompt and response safety and can easily be fine-tuned to create a new taxonomy depending on application needs. As a starting point, the new Llama Guard 2 uses the recently announced MLCommons taxonomy, in an effort to support the emergence of industry standards in this important area. Additionally, CyberSecEval 2 expands on its predecessor by adding measures of an LLM’s propensity to allow for abuse of its code interpreter, offensive cybersecurity capabilities, and susceptibility to prompt injection attacks (learn more in our technical paper ). Finally, we’re introducing Code Shield which adds support for inference-time filtering of insecure code produced by LLMs. This offers mitigation of risks around insecure code suggestions, code interpreter abuse prevention, and secure command execution.

With the speed at which the generative AI space is moving, we believe an open approach is an important way to bring the ecosystem together and mitigate these potential harms. As part of that, we’re updating our Responsible Use Guide (RUG) that provides a comprehensive guide to responsible development with LLMs. As we outlined in the RUG, we recommend that all inputs and outputs be checked and filtered in accordance with content guidelines appropriate to the application. Additionally, many cloud service providers offer content moderation APIs and other tools for responsible deployment, and we encourage developers to also consider using these options.

Deploying Llama 3 at scale

Llama 3 will soon be available on all major platforms including cloud providers, model API providers, and much more. Llama 3 will be everywhere .

Our benchmarks show the tokenizer offers improved token efficiency, yielding up to 15% fewer tokens compared to Llama 2. Also, Group Query Attention (GQA) now has been added to Llama 3 8B as well. As a result, we observed that despite the model having 1B more parameters compared to Llama 2 7B, the improved tokenizer efficiency and GQA contribute to maintaining the inference efficiency on par with Llama 2 7B.

For examples of how to leverage all of these capabilities, check out Llama Recipes which contains all of our open source code that can be leveraged for everything from fine-tuning to deployment to model evaluation.

What’s next for Llama 3?

The Llama 3 8B and 70B models mark the beginning of what we plan to release for Llama 3. And there’s a lot more to come.

Our largest models are over 400B parameters and, while these models are still training, our team is excited about how they’re trending. Over the coming months, we’ll release multiple models with new capabilities including multimodality, the ability to converse in multiple languages, a much longer context window, and stronger overall capabilities. We will also publish a detailed research paper once we are done training Llama 3.

To give you a sneak preview for where these models are today as they continue training, we thought we could share some snapshots of how our largest LLM model is trending. Please note that this data is based on an early checkpoint of Llama 3 that is still training and these capabilities are not supported as part of the models released today.

We’re committed to the continued growth and development of an open AI ecosystem for releasing our models responsibly. We have long believed that openness leads to better, safer products, faster innovation, and a healthier overall market. This is good for Meta, and it is good for society. We’re taking a community-first approach with Llama 3, and starting today, these models are available on the leading cloud, hosting, and hardware platforms with many more to come.

Try Meta Llama 3 today

We’ve integrated our latest models into Meta AI, which we believe is the world’s leading AI assistant. It’s now built with Llama 3 technology and it’s available in more countries across our apps.

You can use Meta AI on Facebook, Instagram, WhatsApp, Messenger, and the web to get things done, learn, create, and connect with the things that matter to you. You can read more about the Meta AI experience here .

Visit the Llama 3 website to download the models and reference the Getting Started Guide for the latest list of all available platforms.

You’ll also soon be able to test multimodal Meta AI on our Ray-Ban Meta smart glasses.

As always, we look forward to seeing all the amazing products and experiences you will build with Meta Llama 3.

Our latest updates delivered to your inbox

Subscribe to our newsletter to keep up with Meta AI news, events, research breakthroughs, and more.

Join us in the pursuit of what’s possible with AI.

Product experiences

Foundational models

Latest news

Meta © 2024