How much does Ternary Bonsai 2 9B cost?

Ternary Bonsai 2 9B costs $0.08/M input tokens and $0.13/M output tokens, with separate rates for Cache Read at $0.04/M tokens.

What is the context length of Ternary Bonsai 2 9B?

Ternary Bonsai 2 9B has a 262,144 token context window. It supports up to 65,536 completion tokens.

Does Ternary Bonsai 2 9B support tool calling and structured outputs?

Yes. Ternary Bonsai 2 9B accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.

What inputs and outputs does Ternary Bonsai 2 9B support?

Ternary Bonsai 2 9B accepts text and images as input and returns text.

Which providers serve Ternary Bonsai 2 9B?

Ternary Bonsai 2 9B is served by 1 provider on OpenRouter: Darkbloom.

What other text models does PrismML have?

Ternary Bonsai 2 27B is another text model from PrismML.

When was Ternary Bonsai 2 9B released?

Ternary Bonsai 2 9B was released on October 16, 2026.

PrismML: Ternary Bonsai 2 9B

prism-ml/ternary-bonsai-2-9b

Model weights

Compare

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 inference. It accepts text and image input. Its 262K-token context window supports long conversations and document-heavy workflows, with up to 64K output tokens per response.

Modalities

In / out price

$0.08 / $0.13per 1M

Context

262K

Released

Oct 16, 2026

Providers

This model is hosted by one provider. OpenRouter forwards every request without routing.

Latency / throughput


	$0.08	$0.13	$0.04	0.80s	70 tok/s	99.20%

Input $0.08Output $0.13
70 tok/s99.20% uptime

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted average

Input

$0.07511/M tokens

Output

$0.1299/M tokens

Ternary Bonsai 2 9B — Price history

Price history

No effective price data for this selection

		$0.0751	$0.130	11.9%	100.0%

Effective in $0.0751Effective out $0.130
Token share
100.0%

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Uptime (3d)

100.00%

Availability (3d)

98.63%

Availability over the last 3 days

Last 72 hours

Availability 98.63%

3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability

99.25%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Pegasus weekly report classify80

new

31.7Mtokens

OpenClaw

OpenClaw is an open-source AI agent that connects to your messaging apps and takes real actions on your behalf, from running commands and browsing the web to managing files and sending emails.

14.7Mtokens

Agent Zero

Build autonomous AI agents effortlessly.

8.2Mtokens

Hermes Agent

Hermes Agent is an open-source, self-improving AI agent by Nous Research that runs persistently with memory across sessions, and builds reusable skills from experience. It comes with 40+ built-in tools, including web search, browser automation, and vision, plus scheduled automations and subagents.

5.78Mtokens

TrialBox mlbench

new

4.65Mtokens

Rest of OpenRouter

12.6M

Top 5 Apps

2.58M

Not currently available through EU in-region routing. In-region routing docs

More models from PrismML

Ternary Bonsai 2 27B

Bonsai 2 27B is a 27B-parameter reasoning model from PrismML derived from Qwen3.8-27B. It supports coding, mathematics, tool calling, and image understanding with a 262K-token context window. Ternary compression shrinks the language-model weights to roughly 8.5 GB while retaining 98.2% of the base model's average score across PrismML's 14 thinking-mode benchmarks, enabling efficient inference on consumer hardware. The model thinks by default and defaults to xhigh reasoning effort.

Text262K context$0.075 / $0.50

PrismML: Ternary Bonsai 2 9B

Providers