---
title: mistralai/Mistral-Large-4-1T-A52B
url: https://recentmodel.com/models/mistralai/Mistral-Large-4-1T-A52B/
status: just landed
published: 2026-09-30T18:35:13Z
updated: 2026-10-30T11:19:53Z
source: https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B
---

# mistralai/Mistral-Large-4-1T-A52B

Mistral Large 4 is our largest and most capable model to date: a 1 trillion-parameter natively multimodal Mixture-of-Experts model with 49 billion active parameters per token (52 billion including embeddings and output layers), trained from scratch on 3,800 NVIDIA Grace Blackwell GPUs in Mistral's… Mixture-of-experts, 52B active (128 experts, 4 per token). Context: 1M tokens (config). License: other. Vendor-reported: "While a generalist model, it shows especially good performance on workloads such as cybersecurity, finance, and law, and it surpasses frontier closed models on visual grounding." Vendor-reported: "Vision: analyzes images, charts, technical drawings, and documents, with state-of-the-art visual grounding among open weights."

- Vendor-reported: While a generalist model, it shows especially good performance on workloads such as cybersecurity, finance, and law, and it surpasses frontier closed models on visual grounding.
- Vendor-reported: Vision: analyzes images, charts, technical drawings, and documents, with state-of-the-art visual grounding among open weights.

- **Org:** mistralai
- **Released:** 2026-09-30
- **Status:** just landed
- **License:** other (restricted)
- **Parameters:**  total, 52.0B active
- **Architecture:** MoE · 128 experts, 4/token · MistralLarge4ForConditionalGeneration
- **Context:** 1,048,576 tokens
- **Task:** image-text-to-text · vision
- **Signal:** 1278 HF likes · 1239 downloads

## Runs on

real quant files; sizing calculation, not tested.

- Q4 ~606.5 GB: no listed device
- Q8 ~1119.1 GB: no listed device
- FP16 ~2104.8 GB: no listed device

## Links

- [Hugging Face](https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B)
- [Ollama](https://ollama.com/library/mistral-large-4)
- [GGUF: ggml-org/Mistral-Large-4-1T-A52B-GGUF](https://huggingface.co/ggml-org/Mistral-Large-4-1T-A52B-GGUF)
- [quant: mistralai/Mistral-Large-4-1T-A52B-NVFP4](https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B-NVFP4)
- [MLX: mlx-community/Mistral-Large-4-1T-A52B-Text-2bit](https://huggingface.co/mlx-community/Mistral-Large-4-1T-A52B-Text-2bit)
- [MLX: mlx-community/Mistral-Large-4-1T-A52B-Text-3bit](https://huggingface.co/mlx-community/Mistral-Large-4-1T-A52B-Text-3bit)
- [MLX: mlx-community/Mistral-Large-4-1T-A52B-Text-4bit](https://huggingface.co/mlx-community/Mistral-Large-4-1T-A52B-Text-4bit)
- [Unsloth: unsloth/Mistral-Large-4-1T-A52B-FP8](https://huggingface.co/unsloth/Mistral-Large-4-1T-A52B-FP8)
- [GGUF: unsloth/Mistral-Large-4-1T-A52B-GGUF](https://huggingface.co/unsloth/Mistral-Large-4-1T-A52B-GGUF)
- [Unsloth: unsloth/Mistral-Large-4-1T-A52B-NVFP4](https://huggingface.co/unsloth/Mistral-Large-4-1T-A52B-NVFP4)