Best latest baseline cardiology model available today

other models from Llama or mistrial which are specific to medical field?

Yeah. It’s safest to search using the leaderboard, but it’s quicker to search for Hubs using the keyword med.

Here is the ranked shortlist of medical Llama- and Mistral-based models on Hugging Face that are worth knowing first.

I am ranking for practical starting value , not just novelty. That means I am favoring models that look like real baselines, have usable model cards, and are broad enough for general medical or cardiology-adjacent work. I am not counting quantizations, one-off adapters, or tiny community forks as separate core entries. (Hugging Face)

Start here first

1. m42-health/Llama3-Med42-8B

This is the best Llama-based general medical baseline in the shortlist. The card says Med42-v2 is a suite of clinically aligned Llama-3 models in 8B and 70B , trained on about 1B tokens , with intended uses including medical QA and patient-record summarization. If you want one broad medical Llama model to test first, this is the cleanest starting point. The 70B version is stronger, but the 8B model is the more practical baseline. (Hugging Face)

2. HPAI-BSC/Llama3.1-Aloe-Beta-8B

This is the strongest newer Llama-based research alternative in the shortlist. The card says Aloe is trained on 20 medical tasks , that the Beta release is the latest Aloe iteration, and that the 8B Beta expanded training to 1.8B tokens across more task types such as summarization, diagnosis, classification, and treatment recommendation. The main drawback is licensing: Aloe modifications are under CC-BY-NC-4.0 , so it is non-commercial unless that fits your use case. (Hugging Face)

3. BioMistral/BioMistral-7B

This is the best Mistral-based medical text baseline here. The card says BioMistral is an Apache-2.0 open-source medical model built on Mistral-7B-Instruct-v0.1 , further pre-trained on PubMed Central , and evaluated on 10 established medical QA tasks in English. If you specifically want a Mistral-family medical checkpoint, this is the first one to try. The caution is also explicit in the card: it is positioned as a research tool , not a clinically validated deployment model. (Hugging Face)

4. johnsnowlabs/JSL-MedLlama-3-8B-v2.0

This is a solid Llama-based medical text model with visible benchmark numbers on the card, including MedMCQA, MedQA, PubMedQA, and MMLU medical subsets. I rank it below Med42 and Aloe because the license is more restrictive, CC-BY-NC-ND-4.0 , and the card is lighter on training details. Still, it is a legitimate model, not a throwaway community fine-tune. (Hugging Face)

5. dmis-lab/meerkat-7b-v1.0

This is the most interesting reasoning-focused Mistral-based medical model in the shortlist. The card says it is based on Mistral-7B-v0.1 , trained on synthetic chain-of-thought data derived from 18 medical textbooks , and claims to be the first 7B medical model to exceed the 60% USMLE passing threshold. I would test it when you care about exam-style reasoning or case-style dialogue more than broad production fit. (Hugging Face)

Test later or only if the task matches

6. UMCU/CardioLlama.nl_clinical

This is the most clearly cardiology-specific Llama model I could verify, but it is also very narrow. The Hugging Face material shows it is based on Llama-3.2-1B-Instruct , domain-adapted on a Dutch medical corpus , then further pre-trained on 5 million cardiology records mixed with broader Dutch medical text. It was also updated October 29, 2025. I would only move this high in the ranking if your work is specifically Dutch cardiology text. For English general medical work, it is too specialized and too small to be the first baseline. (Hugging Face)

7. microsoft/llava-med-v1.5-mistral-7b

This is the best Mistral-based biomedical vision-language model in the shortlist, not the best general medical text model. The card says it uses Mistral-7B-Instruct-v0.2 , was trained in April 2024 , builds on the PMC-15M biomedical image-text dataset, and is intended for research use only , not clinical care or deployed use. Use it for biomedical VQA and image-text experiments, not as a general cardiology text baseline. (Hugging Face)

8. ContactDoctor/Bio-Medical-MultiModal-Llama-3-8B-V1

This is a multimodal Llama-3 medical model trained on a custom biomedical text-and-image dataset with 500,000+ entries. The card positions it for biomedical research, education, and decision-support-style use cases, but it also uses a non-commercial custom license and the validation story is lighter than the higher-ranked entries. I would treat it as a niche multimodal experiment, not the first broad medical baseline. (Hugging Face)

The simple decision rule

If you want the cleanest answer:

• Best Llama medical model to start with: Med42-v2 8B. (Hugging Face)
• Best newer Llama research alternative: Llama3.1-Aloe-Beta-8B. (Hugging Face)
• Best Mistral medical text model: BioMistral-7B. (Hugging Face)
• Best Mistral medical multimodal model: LLaVA-Med v1.5 Mistral-7B , but only for research. (Hugging Face)
• Best cardiology-specific Llama niche model: CardioLlama.nl_clinical , only if your domain is Dutch cardiology text. (Hugging Face)

My practical recommendation

For a general medical or cardiology-adjacent text project , I would test them in this order:

1. m42-health/Llama3-Med42-8B
2. HPAI-BSC/Llama3.1-Aloe-Beta-8B
3. BioMistral/BioMistral-7B
4. johnsnowlabs/JSL-MedLlama-3-8B-v2.0
5. dmis-lab/meerkat-7b-v1.0 (Hugging Face)

For a cardiology-specific direction, I would still start from one of the broad medical baselines above unless you specifically need Dutch cardiology , in which case CardioLlama becomes much more relevant. (Hugging Face)