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MASHBOX Labs

MASHBOX Labs makes open models run faster and cheaper on TPUs and accelerated hardware, as well as exploring the future of the intersection of AI and gaming.

Quickstart • Models • Docs • Hugging Face • Coding agents

Licence: Apache-2.0 TPU v6e Python 3.12 Hugging Face X

Qwen3.8-27B on one TPU v6e chip

Qwen3.8-27B on one TPU v6e chip: first-time install to first answer (sped up 10x).

Quickstart

From your own machine, with the Google Cloud CLI set up (docs/google-cloud.md does that from a new Google account). This runs Qwen3.8-27B on one TPU v6e chip:

gcloud compute tpus tpu-vm create mashbox-1 --zone=us-east5-b --accelerator-type=v6e-1 --version=v2-alpha-tpuv6e
gcloud compute tpus tpu-vm ssh mashbox-1 --zone=us-east5-b --command='python3 -m pip install uv && python3 -m uv tool install --python 3.12 "mashbox[tpu]" && ~/.local/bin/mashbox run qwen3-8-27b --prompt "Write a haiku about the sea."'
gcloud compute tpus tpu-vm delete mashbox-1 --zone=us-east5-b --quiet

The chip's system Python is 3.10 and JAX for TPU needs 3.12, so the second line installs uv, which brings its own Python 3.12 and puts the mashbox command in ~/.local/bin. The first run downloads the 26.9 GB weights file: on our new chip (28 October 2026) the model's first start took 138 s, most of it the download, and later starts took 6.6 s. If the create command says the zone has no capacity, use another zone from step 6 of the setup guide in all three lines.

The chip bills from create to delete: one TPU v6e chip is $2.70 an hour at Google's on-demand list price (read 19 October 2026). To serve Qwen3.8-27B with an OpenAI-compatible API instead, see docs/models/qwen3-8-27b.md.

Models

Model What it does Chips Measured Weights
Qwen3.8-27B
by Qwen
LLM: text in, text out TPU v6e: passing, 2026-10-28
TPU v5e: not supported
38.1 vs 31.4 tok/s vs vLLM on the same chip, 1 request at a time; 130.1 vs 1,606.7 s first start to ready, weights on disk, vs vLLM on the same chip (TPU v6e-1, 2026-10-28). All results Qwen3.8-27B-TPU

Coming soon: Hy-Nomas by Tencent Hunyuan (world model: text and movement keys in, video out).

Every number names the chip it was measured on; each model's guide holds the full record. Options for any model: ~/.local/bin/mashbox run <model> --help.

Results

Each chart names its measurement date (UTC) and the hardware on both sides.

Qwen3.8-27B: time to ready on one TPU v6e-1. Measured 2026-10-28 03:53-05:39 UTC on one TPU v6e-1 (Google Cloud, us-east5-b) vs the same TPU v6e-1. MASHBOX measurement ledger CH-01.

Qwen3-30B-A3B: quality vs file size, 20 files. Measured 2026-10-27 07:15 UTC on a frozen llama.cpp CPU scorer (16 threads, AMD EPYC 7502P / 7B13) vs the same scorer and the same 10,240 positions for every rival file. MASHBOX measurement ledger CH-04.

Qwen3-30B-A3B is not in this package yet: this chart is file quality from our quantization work, scored the same way for every file.

What you get

  • One command per model. mashbox run <model> downloads the weights, checks every file's sha256, loads the model and serves it.
  • Fits on fewer chips. Qwen3.8-27B runs on a single TPU v6e chip (32 GB) from a 26.94 GB weights file at 8.01 bits per weight, with 99.72% top-1 agreement against Qwen's own bf16 weights.
  • Fast starts. Models ship their compiled TPU kernels, and Qwen3.8-27B also ships a precompiled compile cache for TPU v6e, so a restart is ready in seconds (6.6 s for Qwen3.8-27B on TPU v6e-1, measured 28 October 2026).
  • An OpenAI-compatible server for the language models, with batching: 8 requests at once share the chip.
  • Works with Claude Code, Codex and Pi. The server also speaks the Anthropic Messages and OpenAI Responses APIs, so coding agents can use a model you serve as their LLM: Use with coding agents.
  • Docs for coding agents. AGENTS.md gives an agent the rules and the steps to set up a chip, run a model and delete the chip; llms.txt lists the docs.
  • Named files. Every weights file on Hugging Face is named by its type (for example Qwen3.8-27B-BQ8_R.bshj), with size, bits per weight and measured quality next to it.

TPU v6e and v5e

TPU v6e TPU v5e
Memory per chip 32 GB 16 GB
Memory bandwidth per chip 1,638 GBps 800 GiBps
Peak bf16 per chip 918 TFLOPs 197 TFLOPs
Peak int8 per chip 1,836 TOPs 393 TOPs
Create with --accelerator-type=v6e-1 --version=v2-alpha-tpuv6e --accelerator-type=v5litepod-1 --version=v2-alpha-tpuv5-lite
Zones that worked for us us-east5-b, europe-west4-a us-central1-a

v6e is the default. A model runs on v5e when its weights and working memory fit in 16 GB; the models table says which chips each model passed on. Specs from Google's v6e and v5e pages, read 28 October 2026. More in docs/chips.md.

Open code, compiled kernels

The source of the model ports, CLI, runtime, demo apps and docs is in this repo, under Apache-2.0. Each model ships with its own compiled TPU kernels (our Culet kernels) and, where we built one, a precompiled compile cache, only what that model needs: mashbox run downloads them from the model's Hugging Face repo and checks them against the sha256 in models.json. Models that list plain JAX as tested also run without them, slower. The compiled files are under the MASHBOX Kernel Licence: free for personal use, research and evaluation, and for any use by companies under US$1M annual revenue. Larger companies in production: hello@mashbox.gg.

Coding agents

Use a model as your agent's LLM. Claude Code, Codex and Pi work with every LLM that mashbox run serves: start the server, open the tunnel, set the agent's base URL. Settings for each agent and what we measured: Use with coding agents.

Let an agent set it up. AGENTS.md gives an agent the rules and the steps, from a Google account to a run and a deleted chip, and tells it to ask you before anything that costs money. llms.txt lists the docs.

Docs mashbox.gg/docs
Models and weights huggingface.co/mashbox-labs
News x.com/mashboxgg
Bugs and model requests GitHub issues, see CONTRIBUTING.md
Security reports SECURITY.md
Companies hello@mashbox.gg

Licence

Our code is under the Apache License 2.0. The compiled kernels and compile cache are under the MASHBOX Kernel Licence. Model weights keep each model's own licence, shown on its Hugging Face card and kept unchanged in licenses/. Details: docs/licence.md.

Citation

@software{mashbox,
  author = {{MASHBOX Labs}},
  title = {mashbox: open models that run faster and cheaper},
  url = {https://github.com/mashbox-labs/mashbox},
  year = {2026}
}

Thank you

  • Tencent Hunyuan for Hy-Nomas and Qwen for Qwen3.8-27B, and for releasing their weights.
  • The JAX and Pallas teams, and Google Cloud TPU.
  • Hugging Face for hosting the weights and uv for a one-line Python 3.12.

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