Moduck

Phocinae: Phocinae Largha 150M v1

Encoder decision model that answers typed questions (noul, choice, score) over text with calibrated probabilities, on CPU and GPU

Model lab
Phocinae
Model family
—

Model resources

Modalitiestext → text
Context window8,192
Maximum output—

Quickstart

Use your Moduck API Key, set the API base URL to https://api.moduck.ai/v1, and set the model parameter to phocinae/phocinae-largha-150m-v1.

import os
import requests

base_url = "https://api.moduck.ai/v1"
api_key = os.environ["MODUCK_API_KEY"]
model_id = "phocinae/phocinae-largha-150m-v1"

response = requests.post(
    f"{base_url}/chat/completions",
    headers={
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json",
    },
    json={
        "model": model_id,
        "messages": [{"role": "user", "content": "Hello!"}],
        "stream": False,
    },
    timeout=60,
)
response.raise_for_status()
print(response.json())

Use the familiar OpenAI-style chat request format to make model integration easier.

Phocinae Largha 150M v1 API Pricing

Price currently unavailable

Performance

Measured on the Moduck gateway across live traffic, hour by hour over the last 24 hours. Time to first token is how long before anything appears; throughput is how fast the answer is written after that; end-to-end latency is the whole round trip. Figures are medians unless the card says otherwise.

Performance trends

Request throughput14.2 requests/minCurrent
Queue wait0.9 sCurrent
Completion time6.0 sCurrent
Request throughput
Current14.2 requests/min
Window average15.0 requests/min
Queue wait
Current0.9 s
Window average0.9 s
Completion time
Current6.0 s
Window average6.0 s
Tail completion time (P99)
Current13.6 s
Window average13.9 s
Retry rate
Current1.0%
Window average1.1%
Error rate
Current0.0%
Window average0.1%

Availability

Uptime is the share of time at least one provider serving this model responded. Availability is stricter: the share of requests actually served. A provider that answers but fails part of the traffic lowers availability without lowering uptime. Both cover the last three days.

Uptime100%At least one provider responded
Availability100%Requests actually served
Error rate0%Share of failed requests
Served requests, hour by hour
24 hours agoNow

Phocinae Largha 150M v1 Compare models

ModelInput priceOutput priceContext windowCapabilities
Phocinae Largha 150M v1This pagePrice currently unavailablePrice currently unavailable8,192Specialized model
Jev 1.14USD 0.0336 / 1M tokens · Context ≤ 32000 tokensNot billed on output64,000Specialized model
Drex 2.0USD 0.048 / 1M tokensNot billed on output131,072Specialized model
Liquid d1USD 0.016 / 1M tokensNot billed on output65,536Specialized model
Drex 1.5USD 0.032 / 1M tokens · Context ≤ 131072 tokensNot billed on output139,264Specialized model

Model specifications

Input
text
Output
text
Context window
8,192
Maximum output
—
Release date
2026-10-08
Attachments
No
Reasoning
No
Tool calling
No
Structured output
Yes
Temperature setting
No
Open weights
Yes

Frequently asked questions

What is Phocinae Largha 150M v1 for?

Encoder decision model that answers typed questions (noul, choice, score) over text with calibrated probabilities, on CPU and GPU

What inputs and outputs does Phocinae Largha 150M v1 support?

Recorded inputs: text; outputs: text.

How is Phocinae Largha 150M v1 priced?

This page does not list a price for this model yet.

What specifications are recorded for Phocinae Largha 150M v1?

Current model records list Context window 8,192 tokens.

What model parameter does the Quickstart use?

The example uses phocinae/phocinae-largha-150m-v1. This value comes from the page identifier and is not confirmed as a callable Moduck public ID.

Can I call this model through the Moduck API now?

This page has no verified Moduck API call for this model. A Quickstart example or reserved ID does not establish access; check the models available to your account.