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Centering AI research on efficiency. https://t.co/88MQHGCeFD

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We also tested Ternary Bonsai 2 27B on the 2026 IMO problems against full-precision Qwen3.8 27B (54GB) and Gemma 4 12B QAT (~7GB). No internet. No tools. 131K-token reasoning budget. Bonsai scored in the upper end of the human bronze-medal range and retained 95% of Qwen’s IMO score, while completing the problems in 70% of the time. Code:

We also tested Ternary Bonsai 2 27B on the 2026 IMO problems against full-precision Qwen3.8 27B (54GB) and Gemma 4 12B QAT (~7GB). No internet. No tools. 131K-token reasoning budget. Bonsai scored in the upper end of the human bronze-medal range and retained 95% of Qwen’s IMO score, while completing the problems in 70% of the time. Code:

34,109 views • 9 days ago

Here is Ternary Bonsai 27B running an end-to-end agentic workflow locally with Hermes on an NVIDIA GeForce RTX 5090 GPU. The model reasons, calls tools, reads outputs, modifies files, and surfaces insights - all on consumer hardware, while all private files, intermediate states, and iterations remain local.

Here is Ternary Bonsai 27B running an end-to-end agentic workflow locally with Hermes on an NVIDIA GeForce RTX 5090 GPU. The model reasons, calls tools, reads outputs, modifies files, and surfaces insights - all on consumer hardware, while all private files, intermediate states, and iterations remain local.

154,473 views • 2 months ago

1-bit Bonsai 8B running locally on an M4 Pro (MLX) alongside a standard 16-bit 8B model. Same class of model, very different deployment profile: far lower memory use and substantially higher throughput.

93,717 views • 6 months ago

The phone threshold is even harder than the storage number suggests. A phone exposes only part of its memory to an application, and the model must share that budget with its KV cache, activations, runtime, and the rest of the product. At 3.9 GB, 1-bit Bonsai 27B clears that threshold with room to work, making 27B-class local AI possible on a phone for the first time. (Demo Mode: cached & prefilled image context)

The phone threshold is even harder than the storage number suggests. A phone exposes only part of its memory to an application, and the model must share that budget with its KV cache, activations, runtime, and the rest of the product. At 3.9 GB, 1-bit Bonsai 27B clears that threshold with room to work, making 27B-class local AI possible on a phone for the first time. (Demo Mode: cached & prefilled image context)

33,665 views • 2 months ago

Try Ternary Bonsai 27B directly on Hugging Face , powered by Together AI

Try Ternary Bonsai 27B directly on Hugging Face , powered by Together AI

19,934 views • 2 months ago

We’re also launching Bonsai Studio, an iOS app for trying Bonsai Image 4B directly on your iPhone. Run image generation on-device, with no subscription and no API requests.

We’re also launching Bonsai Studio, an iOS app for trying Bonsai Image 4B directly on your iPhone. Run image generation on-device, with no subscription and no API requests.

14,499 views • 4 months ago

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