Applications

Claude Code ollama launch claude --model MichelRosselli/bonsai-27b

OpenCode ollama launch opencode --model MichelRosselli/bonsai-27b

Hermes Agent ollama launch hermes --model MichelRosselli/bonsai-27b

OpenClaw ollama launch openclaw --model MichelRosselli/bonsai-27b

Bonsai 27B

This is an unofficial Ollama upload of Prism ML’s 1-bit Bonsai 27B model. It packages the Q1_0 language model with the Q8_0 vision projector and uses Ollama’s native Qwen 3.5 renderer and parser for vision, tool calls, and thinking.

Tag	Size	Context	Notes
`latest`	4.4 GB	262,144	Alias of `Q1_0`
`Q1_0`	4.4 GB	262,144	Q1_0 language model with Q8_0 vision projector

Usage

ollama run MichelRosselli/bonsai-27b

ollama run MichelRosselli/bonsai-27b:Q1_0

Model

Item	Specification
Base model	Qwen3.6-27B
Language model	26.9B parameters, Q1_0
Vision projector	460.73M parameters, Q8_0
Context window	262,144 tokens
Ollama version	0.32.5 or newer
Capabilities	Text, vision, tools, thinking

Prism ML describes Bonsai 27B as a binary-weight model with a true 1.125 bits per language-model weight and an approximately 3.9 GB language-model footprint. The published Ollama package is 4.4 GB because it also includes the optional Q8_0 vision projector.

Generation Settings

Parameter	Value
`temperature`	0.7
`top_k`	20
`top_p`	0.95
`min_p`	0.0
`repeat_penalty`	1.0
`num_ctx`	262,144

num_predict remains request-specific. Ollama does not expose a max_p Modelfile parameter.

Notes

This upload uses RENDERER qwen3.5 and PARSER qwen3.5; it does not replace the native Ollama renderer/parser with a custom template.
The Q8_0 multimodal projector is included and image input was runtime-tested.
DSpark is not included because the tested Ollama releases do not support its architecture or expose it through a DRAFT Modelfile directive.
The F16 variant is intentionally not included; Q1_0 is the lightest compatible language-model variant in the source repository.
Text, thinking, structured tool calls, long histories, and front-loaded image prompts were compared with the canonical Hugging Face template.
Ollama cannot exactly represent interleaved text/image ordering, video placeholders, add_vision_id, or preserve_thinking through the native renderer API.
With think=false, Ollama omits reasoning from the current tool-call history where the Hugging Face template preserves it.
Array and object tool arguments differ byte-for-byte only in JSON separator whitespace; schema-aware response parsing reconstructs their types.
A literal complete <tool_call> example in normal answer text may be parsed as a real tool call. An unterminated tool-call block may be discarded by the native parser.

Attribution

All credit for the original model belongs to Prism ML.

Created using Bonsai by Prism ML.

Original resources:

License: Apache 2.0.

Full 27B-class reasoning in binary transformer weights.