---
title: zml/llmd 20261029.0
link: https://zml.ai/posts/llmd-20261029.0/
source: zml-ai
published: 2026-10-29T07:00:00Z
updated: 2026-10-29T07:00:00Z
first_seen: 2026-10-29T20:30:27.834895129Z
summary: 'We are pleased to announce the release of zml/llmd 20261029.0. This week, we are bringing more models: Mistral Large 4 GLM 5.2 and GLM 5.3 series LFM 3 series Mistral Large 4 – Le Chonk In coordination with Mistral, we are pleased to announce Day 0 support for Mistral Large 4. Mistral Large 4 Le Chonk (Le Chonk) is a 1-trillion-parameter multimodal model, now available with improved coding, cybersecurity, and reasoning efficiency. It leads open-weight benchmarks in coding and defensive security while offering three reasoning modes for cost-performance balance. Fully open-weight and European-trained, it empowers sovereign AI with customizable, self-hosted deployment options.'
content: extracted
html: 2026-10-29-zml-llmd-20261029-0.html
remote_preview:
  url: https://zml.ai/og/background_hu_22c0fbe8ede75b88.png
  alt: zml/llmd 20261029.0 — Le Chonk.
---

[Back to posts](https://zml.ai/posts/)

Article

Le Chonk.

October 29, 2026 inference / serving / mistral / chonk / glm / lfm

We are pleased to announce the release of `zml/llmd 20261029.0`. This week, we are bringing more models:

- [Mistral Large 4](https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B)
- [GLM 5.2](https://huggingface.co/collections/zai-org/glm-52) and [GLM 5.3](https://huggingface.co/collections/zai-org/glm-53) series
- [LFM 3](https://huggingface.co/LiquidAI/LFM3-1.7B) series

## Mistral Large 4 – Le Chonk ![](https://zml.ai/posts/llmd-20261029.0/big-cat-icon.svg)

In coordination with Mistral, we are pleased to announce Day 0 support for [Mistral Large 4](https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B).

> Mistral Large 4 Le Chonk (Le Chonk) is a 1-trillion-parameter multimodal model, now available with improved coding, cybersecurity, and reasoning efficiency. It leads open-weight benchmarks in coding and defensive security while offering three reasoning modes for cost-performance balance. Fully open-weight and European-trained, it empowers sovereign AI with customizable, self-hosted deployment options.

[See the press release](https://mistral.ai/news/mistral-large-4-oss/).

The native DSpark Speculative decoding is also supported via the `--speculative-drafter-model=native` flag.

Decode throughput, mistralai/Mistral-Large-4-1T-A52B, bs=1, 4xGB300 (tok/s)

```
$ docker run -p 8000:8000 --shm-size=32GB --gpus=all -e HF_TOKEN -it zmlai/llmd:cuda \
    --model=hf://mistralai/Mistral-Large-4-1T-A52B
```

Sadly, we could not bring it to AMD due to [a bug in the `amdgpu` driver that’s now been fixed but not released](https://www.mail-archive.com/amd-gfx@lists.freedesktop.org/msg152088.html). We are actively [monitoring the situation](https://zml.ai/posts/llmd-20261029.0/monitoring_the_situation.jpeg).

Even though it should work, we haven’t tested it on Google TPUs because, again, we could not get any.

## GLM 5.2 and GLM 5.3

This release also brings support for the [GLM 5.2](https://huggingface.co/collections/zai-org/glm-52) and [GLM 5.3](https://huggingface.co/collections/zai-org/glm-53) series of models.

## LFM 3

This release brings support for the [LFM 3](https://huggingface.co/LiquidAI/LFM3-1.7B) series of models, in all flavours (BF16, FP8 and NVFP4).

This model is great at agentic tasks and following instructions. Combined with our NVFP4 support on Metal, it makes for a great fully local combination, especially when paired with the [Lightpanda MCP](https://lightpanda.io/docs/usage/mcp):

Decode throughput, LiquidAI/LFM3-1.7B, bs=1, zml/llmd 20261029.0, M3 Max (tok/s)

![](https://zml.ai/posts/llmd-20261029.0/dsh.png)

## Try it today

## NVIDIA

```bash
docker run -p 8000:8000 --shm-size=256GB --gpus=all -e HF_TOKEN -it zmlai/llmd:cuda \
    --model=hf://LiquidAI/LFM3-1.7B-FP8
```

## AMD

```bash
docker run -p 8000:8000 --shm-size=256GB --device=/dev/kfd --device=/dev/dri -e HF_TOKEN -it zmlai/llmd:rocm \
    --model=hf://LiquidAI/LFM3-1.7B-FP8
```

## Intel

```bash
docker run -p 8000:8000 --device=/dev/dri -e HF_TOKEN -it zmlai/llmd:oneapi \
    --model=hf://LiquidAI/LFM3-1.7B
```

## Google TPU

```bash
docker run --net=host --privileged -e HF_TOKEN -it zmlai/llmd:tpu \
    --model=hf://LiquidAI/LFM3-1.7B
```

```bash
brew install zml/zml/llmd
llmd --model=hf://LiquidAI/LFM3-1.7B-FP8 --batch-size=4
```