PrismML: Ternary Bonsai 2 9B✓ Catalog verified
Ternary Bonsai 2 9B is PrismML’s compact, open-weight language model for conversational AI, reasoning, and tool use. Built on Qwen3.5, it uses ternary weights packed into 2 bits for efficient...
Overview
Ternary Bonsai 2 9B is PrismML’s compact, open-weight language model for conversational AI, reasoning, and tool use. Built on Qwen3.5, it uses ternary weights packed into 2 bits for efficient...
Access: available through the official Prism ML API. Context window: 262K.
Specifications
| API identifier | prism-ml/ternary-bonsai-2-9b |
| Provider | Prism ML |
| Model type | Multimodal LLM |
| Context window | 262K catalog |
| Input modalities | text · image |
| Output modalities | text |
| Released | Oct 16, 2026 |
| Tokenizer | Qwen |
| Moderated | No |
| Architecture modality | text+image->text |
API defaults
{
"top_k": 20,
"top_p": 0.95,
"temperature": 1
}Pricing
Live pricing components for prism-ml/ternary-bonsai-2-9b as published in the catalog.
| Pricing component | Raw unit price | Normalized | Unit |
|---|---|---|---|
| Prompt tokens | $8e-8 | $0.08 / 1M | Per input token |
| Completion tokens | $1.3e-7 | $0.13 / 1M | Per output token |
| Request fee | N/A | N/A | Per request |
| Image fee | N/A | N/A | Per image unit |
| Web search fee | N/A | N/A | Per search request |
Cost calculator
Estimate monthly spend from your own token volumes.
Estimated Total Cost
$0.07Calculated from current list pricing in the ModelsAtlas catalog.Capabilities
| Capability | Status | What it means |
|---|---|---|
| Visual Understanding | ✓ Supported | Image and document analysis support |
| Audio Processing | Not advertised | Speech and voice aligned flows |
| Tool Calling | ✓ Supported | Supports tools / function calling |
| Self-Hosting | Not advertised | Deploy outside managed APIs |
Capability signals
Directional signals derived from model metadata and capability tags — not official benchmark submissions.
Quick start
Call PrismML: Ternary Bonsai 2 9B through an OpenAI-compatible client.
from openai import OpenAI
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key="YOUR_API_KEY"
)
response = client.chat.completions.create(
model="prism-ml/ternary-bonsai-2-9b",
messages=[{"role": "user", "content": "Explain quantum physics."}]
)
print(response.choices[0].message.content)Alternatives
Closest models by context window from a different provider.
| Model | Provider | Context | Input /1M | Actions |
|---|---|---|---|---|
| AionLabs: Aion 3.5 | Aion Labs | 262K | $3.00 | View → |
| AionLabs: Aion 3.5 Mini | Aion Labs | 262K | $0.70 | View → |
Sources & attribution
Pricing and metadata are maintained in the ModelsAtlas catalog.
Frequently asked questions
How much does PrismML: Ternary Bonsai 2 9B cost?
$0.08 per 1M input tokens and $0.13 per 1M output tokens on the official Prism ML API.
What is the context window of PrismML: Ternary Bonsai 2 9B?
PrismML: Ternary Bonsai 2 9B supports up to 262K tokens of context.
Does PrismML: Ternary Bonsai 2 9B support tool / function calling?
Yes, PrismML: Ternary Bonsai 2 9B supports tool / function calling — you can register tools and the model will emit structured tool calls.
How do I access PrismML: Ternary Bonsai 2 9B?
Use the official Prism ML API with the model id `prism-ml/ternary-bonsai-2-9b`. See the Quick start section above for code examples.