{
  "$type": "site.standard.document",
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  "path": "/t/best-latest-baseline-cardiology-model-available-today/174366#post_4",
  "publishedAt": "2026-03-19T01:40:54.000Z",
  "site": "https://discuss.huggingface.co",
  "tags": [
    "search for Hubs using the keyword med",
    "Hugging Face"
  ],
  "textContent": "> other models from Llama or mistrial which are specific to medical field?\n\nYeah. It’s safest to search using the leaderboard, but it’s quicker to search for Hubs using the keyword med.\n\n* * *\n\nHere is the **ranked shortlist** of **medical Llama- and Mistral-based models on Hugging Face** that are worth knowing first.\n\nI 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)\n\n## Start here first\n\n### 1. **m42-health/Llama3-Med42-8B**\n\nThis 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)\n\n### 2. **HPAI-BSC/Llama3.1-Aloe-Beta-8B**\n\nThis 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)\n\n### 3. **BioMistral/BioMistral-7B**\n\nThis 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)\n\n### 4. **johnsnowlabs/JSL-MedLlama-3-8B-v2.0**\n\nThis 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)\n\n### 5. **dmis-lab/meerkat-7b-v1.0**\n\nThis 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)\n\n## Test later or only if the task matches\n\n### 6. **UMCU/CardioLlama.nl_clinical**\n\nThis 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)\n\n### 7. **microsoft/llava-med-v1.5-mistral-7b**\n\nThis 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)\n\n### 8. **ContactDoctor/Bio-Medical-MultiModal-Llama-3-8B-V1**\n\nThis 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)\n\n## The simple decision rule\n\nIf you want the cleanest answer:\n\n  * **Best Llama medical model to start with:** **Med42-v2 8B**. (Hugging Face)\n  * **Best newer Llama research alternative:** **Llama3.1-Aloe-Beta-8B**. (Hugging Face)\n  * **Best Mistral medical text model:** **BioMistral-7B**. (Hugging Face)\n  * **Best Mistral medical multimodal model:** **LLaVA-Med v1.5 Mistral-7B** , but only for research. (Hugging Face)\n  * **Best cardiology-specific Llama niche model:** **CardioLlama.nl_clinical** , only if your domain is Dutch cardiology text. (Hugging Face)\n\n\n\n## My practical recommendation\n\nFor a **general medical or cardiology-adjacent text project** , I would test them in this order:\n\n  1. **m42-health/Llama3-Med42-8B**\n  2. **HPAI-BSC/Llama3.1-Aloe-Beta-8B**\n  3. **BioMistral/BioMistral-7B**\n  4. **johnsnowlabs/JSL-MedLlama-3-8B-v2.0**\n  5. **dmis-lab/meerkat-7b-v1.0** (Hugging Face)\n\n\n\nFor 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)",
  "title": "Best latest baseline cardiology model available today"
}