Zen 6 Flash

The compact Zen 6 · ternary 27B · 1.77 bits per weight · reads images · fits a laptop

Zen 6 Flash is the ternary build of Zen 6, from Zen LM, the open model family of Zoo Labs Foundation, a 501(c)(3) non-profit. It is chosen for the same two jobs as Zen 6, where the machine is small:

Agentic coding that runs on your own machine, in under 8 GB with its vision projector, on an Apple Silicon laptop or one GPU.
Marketing work, reading images and documents beside the brief.

Zen 6 and Zen 6 Flash are available now; Zen 7 is in research preview: request access. Zen 6 Flash answers on api.hanzo.ai as zen6-flash.

What the files are

Every weight is ternary, the embeddings and the LM head included. The language model holds 26,895,998,464 weights (read from the GGUF tensor table), so a file's bits per weight is its size in bits over that count, and its ratio to FP16 is 53.79 GB (the count × 2 bytes) over its size.

File	Size	Bits per weight	Smaller than FP16
`Ternary-Bonsai-2-27B-PTQ1_0.gguf`, densely packed	5.95 GB	1.77	9.0x
`Ternary-Bonsai-2-27B-PQ2_0.gguf`, one trit per 2-bit slot, read by GPU and Metal kernels as is	7.21 GB	2.14	7.5x
`Ternary-Bonsai-2-27B-mmproj-Q8_0.gguf`, vision projector	629 MB
`Ternary-Bonsai-2-27B-mmproj-BF16.gguf`, vision projector, full precision	931 MB
`Bonsai-2-27B-DFlash2-Q8_0.gguf`, speculative drafter	2.06 GB
`SHA256SUMS`	66 KB


Context	262,144 tokens native; about three layers in four are linear attention
Inputs	text and images
Architecture	GGUF `general.architecture`: `qwen35`

Accuracy against full precision

Suite	FP16	A conventional 2-bit build (IQ2_XXS)	Zen 6 Flash (PQ2_0)	Retained
Average of 14 reasoning tests	86.33	72.59	84.78	98.2%
Math (MathVision, GSM8K)	97.10	79.40	96.57	99.5%
Code (HumanEval, LiveCode)	90.20	74.80	89.42	99.1%
Tool calling and schema adherence	76.80	58.10	74.92	97.6%
Footprint	53.79 GB	8.8 GB	7.21 GB	86.6% smaller

Measured

Apple Silicon M4 / M5 Max (Metal): 47.2 tok/s decode alone, 92.4 tok/s with the drafter; 7.84 GB including the vision projector and a 32K cache.
DGX Spark (CUDA 13.3): 170.04 tok/s decode with the drafter at 54.2% draft acceptance; 32,768 tokens across 4 parallel slots in under 12 GB.

Serve it

llama.cpp, with the vision projector and the drafter:

llama-server \
  -m Ternary-Bonsai-2-27B-PQ2_0.gguf \
  --mmproj Ternary-Bonsai-2-27B-mmproj-Q8_0.gguf \
  -md Bonsai-2-27B-DFlash2-Q8_0.gguf \
  --spec-draft-n-max 3 \
  -c 32768 \
  --port 8080

On a Mac, one prompt:

llama-cli \
  -m Ternary-Bonsai-2-27B-PQ2_0.gguf \
  --mmproj Ternary-Bonsai-2-27B-mmproj-Q8_0.gguf \
  -p "<image>\nDescribe the system architecture shown in this diagram in detail."

Citation

@misc{zenlm2026zen6flash,
  title  = {Zen 6 Flash},
  author = {Zen LM},
  year   = {2026},
  publisher = {Zoo Labs Foundation}
}

License & attribution

Apache-2.0; see LICENSE. Zen 6 Flash is Ternary Bonsai 2 27B by prism-ml (prism-ml/Ternary-Bonsai-2-27B-gguf, Apache-2.0), itself built from Qwen3.8-27B by the Qwen team (Apache-2.0), with the speculative drafter by ProCreations (ProCreations/Ternary-Bonsai-2-27B-DFlash2).