PrismML: Ternary Bonsai 2 9B

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

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...

Price

Input$0.08

per 1M tokens

Output$0.13

per 1M tokens

Compare this model

Providers

Each row is one seller. Prices are the published rate from that source. A dash means that source did not publish the amount. Sorted by a 3:1 blend of input and output.

Provider	Tag	Quant	Input	Output	Context	Uptime	Status	Source
Darkbloom	darkbloom/int4	int4	$0.08/1M	$0.13/1M	262K	100%	Live	openrouter-endpoints

Monthly bill

Token models use the token counts. Image, video, and audio models use units times the flat rate.

Input tokens Output tokens Units

$0.21 at list price for this workload

Cache

Cache read$0.04

per 1M tokens

Every rate

Unit	Input	Output	Flat	Confidence
token	$0.08/1M	$0.13/1M	Not published—	official

Price history

PrismML: Ternary Bonsai 2 9B

input or flat output

Daily snapshots

UTC date	Unit	Input	Output	Flat
2026-10-28	token	$0.08	$0.13	Not published—
2026-10-29	token	$0.08	$0.13	Not published—
2026-10-30	token	$0.08	$0.13	Not published—

Alternatives

Parameters (17)

frequency_penaltyinclude_reasoninglogprobsmax_tokenspresence_penaltyreasoningrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p

Call this model

OpenRouter id prism-ml/ternary-bonsai-2-9b. InferenceList does not send the request.

curl

curl https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"prism-ml/ternary-bonsai-2-9b","messages":[{"role":"user","content":"Hello"}]}'

JavaScript

await fetch("https://openrouter.ai/api/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: "Bearer " + process.env.OPENROUTER_API_KEY,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "prism-ml/ternary-bonsai-2-9b",
    messages: [{ role: "user", content: "Hello" }],
  }),
});

Python

import os, json, urllib.request
req = urllib.request.Request(
    "https://openrouter.ai/api/v1/chat/completions",
    data=json.dumps({"model": "prism-ml/ternary-bonsai-2-9b", "messages": [{"role": "user", "content": "Hello"}]}).encode(),
    headers={"Authorization": "Bearer " + os.environ["OPENROUTER_API_KEY"], "Content-Type": "application/json"},
)
print(urllib.request.urlopen(req).read().decode())

JSON · History JSON