Ternary Bonsai 1.7B Unpacked — Hardware Requirements & GPU Compatibility
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Ternary Bonsai 1.7B Unpacked is a 1.7B-parameter open language model from prism-ml. It supports a context window of up to 32,768 tokens. At Q4_K_M it needs about 1.57 GB of VRAM — see which GPUs and Macs can run it below.
1.2K downloads
5 likesSpecifications
- Publisher
- prism-ml
- Parameters
- 1.7B
- Architecture
- Qwen3ForCausalLM
- Context Length
- 32,768 tokens
- Vocabulary Size
- 151,669
- Release Date
- 2026-04-14
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does Ternary Bonsai 1.7B Unpacked Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 1.3 GB | 4.8 GB | 0.73 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 1.4 GB | 4.9 GB | 0.84 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 1.6 GB | 5.1 GB | 1.03 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 1.8 GB | 5.3 GB | 1.23 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 1.9 GB | 5.5 GB | 1.42 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 2.3 GB | 5.8 GB | 1.72 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 4.0 GB | 7.5 GB | 3.44 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Ternary Bonsai 1.7B Unpacked?
Q4_K_M · 1.6 GBTernary Bonsai 1.7B Unpacked (Q4_K_M) requires 1.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 3+ GB is recommended. Using the full 33K context window can add up to 3.5 GB, bringing total usage to 5.1 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Ternary Bonsai 1.7B Unpacked?
Q4_K_M · 1.6 GB33 devices with unified memory can run Ternary Bonsai 1.7B Unpacked, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomWhere to Download Ternary Bonsai 1.7B Unpacked
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Related Models
Frequently Asked Questions
- How much VRAM does Ternary Bonsai 1.7B Unpacked need?
Ternary Bonsai 1.7B Unpacked requires 1.6 GB of VRAM at Q4_K_M, or 4.0 GB at BF16. Full 33K context adds up to 3.5 GB (5.1 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 1.7B × 4.8 bits ÷ 8 = 1 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 4.1 GB (at full 33K context)
VRAM usage by quantization
Q4_K_M1.6 GBQ4_K_M + full context5.1 GB- What's the best quantization for Ternary Bonsai 1.7B Unpacked?
For Ternary Bonsai 1.7B Unpacked, Q4_K_M (1.6 GB) offers the best balance of quality and VRAM usage. Q5_K_M (1.8 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 1.3 GB.
VRAM requirement by quantization
Q2_K1.3 GBQ4_K_M ★1.6 GBQ5_K_M1.8 GBQ6_K1.9 GBQ8_02.3 GBBF164.0 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Ternary Bonsai 1.7B Unpacked on a Mac?
Ternary Bonsai 1.7B Unpacked requires at least 1.3 GB at Q2_K, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Ternary Bonsai 1.7B Unpacked locally?
Yes — Ternary Bonsai 1.7B Unpacked can run locally on consumer hardware. At Q4_K_M quantization it needs 1.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Ternary Bonsai 1.7B Unpacked?
At Q4_K_M, Ternary Bonsai 1.7B Unpacked can reach ~1857 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~417 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 1.6 × 0.55 = ~1857 tok/s
Estimated speed at Q4_K_M (1.6 GB)
~1857 tok/s~417 tok/s~1388 tok/s~1148 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Ternary Bonsai 1.7B Unpacked?
At Q4_K_M, the download is about 1.03 GB. The full-precision BF16 version is 3.44 GB. The smallest option (Q2_K) is 0.73 GB.
- Which GPUs can run Ternary Bonsai 1.7B Unpacked?
35 consumer GPUs can run Ternary Bonsai 1.7B Unpacked at Q4_K_M (1.6 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 35 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Ternary Bonsai 1.7B Unpacked?
33 devices with unified memory can run Ternary Bonsai 1.7B Unpacked at Q4_K_M (1.6 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.