Identity
- Status
- active
- Developer ID
prism-ml/Ternary-Bonsai-1.7B- Released
- Apr 18, 2026
- Version
- Ternary Bonsai 1.7B
- License
- apache-2.0
PrismMLTernary Bonsai 1.7B
PrismML's smallest ternary Bonsai text model for constrained local inference.
- Token context
- 33K tokens
- Inputs
- Text
- Outputs
- Text
- Released
- Apr 18, 2026
Providers & Pricing
0 current sourced offerings
No Hosted API AvailableThis record is downloadable or self-hosted. Its cost depends on the infrastructure and serving configuration, not a universal model price.
At a Glance
Model Facts
Capacity
- Token context
- 33K tokens
- Maximum output
- Unknown
- Total parameters
- 1.7B
- Active parameters
- Unknown
- Knowledge cutoff
- Not reported
Interface and Access
- Inputs
- Text
- Outputs
- Text
- API available
- No
- Open weights
- Yes
- Self-hostable
- Yes
- Reasoning
- No
- Vision
- No
- Tool calling
- No
- Capabilities
- chat, generation
Technical Specifications
- Weight format
- Ternary Q2_0
- Effective bit width
- 1.58 bits per weight
- Weight size
- 0.46 GB
This page represents one developer model product. Dated API snapshots, serving endpoints, pricing, regions, quantizations, and service tiers attach as versioned aliases or provider details and never create duplicate public model records.
Version Lineage
PredecessorUnknown
SuccessorsUnknown
Aliasesprism-ml/Ternary-Bonsai-1.7B, prism-ml/Ternary-Bonsai-1.7B-gguf, prism-ml/Ternary-Bonsai-1.7B-mlx-2bit
Explicit Unknowns
- Maximum output
- Architecture
- Tokenizer
- Knowledge cutoff
Primary Evidence
Sources and Observation Date
Comparable Peers
Related Model Comparisons
| A | Pair | B | Context |
|---|---|---|---|
Ternary Bonsai 1.7BPrismML | vs |  GPT-6 AstraOpenAI | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs | Claude Fable 5.1Anthropic | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs |  DeepSeek V4.1 FlashDeepSeek | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs | Grok 4.6xAI | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs |  Qwen3.8 MaxQwen | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs |  Kimi K3Moonshot AI | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs |  MiniMax M3MiniMax | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs |  GLM 5.3Z.ai | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs |  Hy4 previewTencent | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs | Seed 2.1 ProByteDance Seed | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs |  Mistral Large 3Mistral AI | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs | cross-developer peerstext | |
Ternary Bonsai 1.7BPrismML | vs |  Nova 2 LiteAmazon | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs | cross-developer peerstext | |
Ternary Bonsai 1.7BPrismML | vs |  ERNIE 5.1Baidu | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs | cross-developer peerstext | |
Ternary Bonsai 1.7BPrismML | vs | cross-developer peerstext | |
Ternary Bonsai 1.7BPrismML | vs |  Phi-4 ReasoningMicrosoft | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs | cross-developer peerstext | |
Ternary Bonsai 1.7BPrismML | vs |  Sonar ProPerplexity | cross-developer peerstext |
Ternary Bonsai 1.7BPrismML | vs | Claude Mythos 5.1Anthropic | cross-developer peerstext |
Questions
Ternary Bonsai 1.7B FAQs
What is Ternary Bonsai 1.7B?+
PrismML's smallest ternary Bonsai text model for constrained local inference. It is developed by PrismML and its current sourced lifecycle status is active.
What inputs and outputs does Ternary Bonsai 1.7B support?+
Ternary Bonsai 1.7B's current record lists Text as input and Text as output.
How much context does Ternary Bonsai 1.7B support?+
The current record lists a 33K-token context window and does not report a maximum output length.
What technical specifications are published for Ternary Bonsai 1.7B?+
Ternary Bonsai 1.7B's developer-published specifications include weight format: Ternary Q2_0; effective bit width: 1.58 bits per weight; weight size: 0.46 GB.
How large is Ternary Bonsai 1.7B?+
The current record lists 1.7B total parameters and an unknown active parameter count. Its architecture is not reported.
What capabilities and tasks does Ternary Bonsai 1.7B support?+
Ternary Bonsai 1.7B's recorded capabilities are chat and generation. Its supported tasks are text.
Is Ternary Bonsai 1.7B available through an API?+
Ternary Bonsai 1.7B is explicitly marked as not API-available in the current record.
How much does Ternary Bonsai 1.7B cost through an API?+
Ternary Bonsai 1.7B has no verified hosted API offering, so no provider token price applies. It is a downloadable or self-hosted artifact whose cost depends on the serving infrastructure and workload.
Can Ternary Bonsai 1.7B be self-hosted?+
Ternary Bonsai 1.7B is an open-weight model. Self-hosting is supported, and the recorded license is apache-2.0.
Does Ternary Bonsai 1.7B have related versions or aliases?+
No predecessor is recorded. No successor is recorded. Recorded aliases are prism-ml/Ternary-Bonsai-1.7B, prism-ml/Ternary-Bonsai-1.7B-gguf, and prism-ml/Ternary-Bonsai-1.7B-mlx-2bit.