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Bonsai 27B
About Bonsai 27B
Bonsai 27B is an AI model developed by PrismML, in the multimodal category, released in 2026, made available as an open-source model with 27B params. PrismML's Bonsai 27B is an extreme quantization of Qwen 3.6 27B: a 1-bit build at 3.9GB retaining ~90% quality and a ternary build at 5.9GB retaining ~95%. Small enough for phone deployment while staying multimodal with full 262K context.
On this page you'll find Bonsai 27B's full specifications, including a context window of 262K tokens. Review provider pricing and benchmark scores below, or compare Bonsai 27B head-to-head with other multimodal models.
Run Bonsai 27B locally — what to buy
Share this build ↗Sized to what Bonsai 27B actually needs (~262k context at Q4), not to the biggest GPU: Good = cheapest that runs it, Better = best value, Best = most headroom. Speed is a hardware estimate; anything past ~120 tok/s is shown as instant.
Software support
✓ measured · · compatible · — not supported. Informational only — speed is hardware-based.
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Frequently asked questions
What is Bonsai 27B? ▶
PrismML's Bonsai 27B is an extreme quantization of Qwen 3.6 27B: a 1-bit build at 3.9GB retaining ~90% quality and a ternary build at 5.9GB retaining ~95%. Small enough for phone deployment while staying multimodal with full 262K context. It is tracked on GenAIList with its specifications, benchmark scores and provider pricing.
Who created Bonsai 27B? ▶
Bonsai 27B was developed by PrismML and released in 2026.
Is Bonsai 27B open source or proprietary? ▶
Bonsai 27B is released as open source — its weights are publicly available to download, run locally and fine-tune.
What is Bonsai 27B's context window? ▶
Bonsai 27B supports a context window of 262K tokens, and has 27B params.
How much does Bonsai 27B cost? ▶
Pricing for Bonsai 27B depends on the provider. See the providers table on this page for the latest API rates.
How does Bonsai 27B perform on benchmarks? ▶
Benchmark scores for Bonsai 27B are listed on this page as they are published. You can compare it head-to-head with other models on the GenAIList compare tool.
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