UnslopNemo 12B API: toman pricing and code
thedrummer/unslopnemo-12b
toolsjsonYou are billed for the usage the request actually reported. Prices follow the market.Pricing and top-ups
UnslopNemo 12B example: JSON output against a schema
The example is picked from this model's own capabilities. Drop in your key and it runs as is.
from openai import OpenAI
import json
client = OpenAI(base_url="https://api.uttapen.ir/v1", api_key="sk-up-…")
schema = {
"name": "ticket",
"schema": {
"type": "object",
"properties": {
"category": {"type": "string", "enum": ["fani", "mali", "forush"]},
"priority": {"type": "integer", "minimum": 1, "maximum": 5},
"summary": {"type": "string"},
},
"required": ["category", "priority", "summary"],
"additionalProperties": False,
},
"strict": True,
}
resp = client.chat.completions.create(
model="thedrummer/unslopnemo-12b",
messages=[{"role": "user", "content": "Ticket: "For two days I cannot download my invoice and I was charged twice.""}],
response_format={"type": "json_schema", "json_schema": schema},
)
print(json.loads(resp.choices[0].message.content))import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.uttapen.ir/v1", apiKey: "sk-up-…" });
const resp = await client.chat.completions.create({
model: "thedrummer/unslopnemo-12b",
messages: [{ role: "user", content: "Ticket: "For two days I cannot download my invoice and I was charged twice."" }],
response_format: {
type: "json_schema",
json_schema: {
name: "ticket",
strict: true,
schema: {
type: "object",
properties: {
category: { type: "string", enum: ["fani", "mali", "forush"] },
priority: { type: "integer", minimum: 1, maximum: 5 },
summary: { type: "string" },
},
required: ["category", "priority", "summary"],
additionalProperties: false,
},
},
},
});
console.log(JSON.parse(resp.choices[0].message.content));curl https://api.uttapen.ir/v1/chat/completions \
-H "Authorization: Bearer sk-up-…" \
-H "Content-Type: application/json" \
-d '{
"model": "thedrummer/unslopnemo-12b",
"messages": [{"role": "user", "content": "Classify the ticket and give it a priority from 1 to 5."}],
"response_format": {"type": "json_object"}
}'What is UnslopNemo 12B good for?
UnslopNemo 12B is one of Thedrummer's models. Put "thedrummer/unslopnemo-12b" in the model field and the rest of your code stays as it is. UnslopNemo 12B keeps 1,024,000 tokens in view at once, and that number is what caps the conversation history in your product. A single response can run to 819,200 tokens. On price it sits in the "very cheap" band — cheaper than 71 and dearer than 335 of the other paid models in the catalogue.
What it can do beyond plain text: it supports tool calling, so it can invoke your own functions with valid arguments; it returns schema-valid JSON through response_format, ready to hand to your code. All of it works through the standard parameters of the official OpenAI SDK — no custom client, no wrapper.
Pricing is 116,050 toman per 1M input tokens and 116,050 per 1M output tokens. A 1,000-word round trip on UnslopNemo 12B lands near 302 toman. You are always charged for the usage the request actually reported, never for the estimate, and a failed request costs nothing.
The closest alternative with the same capabilities from a different provider is DeepSeek V3.2: UnslopNemo 12B works out roughly 1.2× more expensive, and its context window is larger. Both run on the same key and the same code, so trying the other one is a single string change.
To make the figure concrete: 100,000 toman of credit buys roughly 331 thousand-word requests on UnslopNemo 12B, and every 1,000 toman is about 3,311 words of round trip. A job with one million input tokens and one million output tokens comes to 232,100 toman in total. Filling this model's 1,024,000-token window costs 118,835 toman on the input side alone, which is the real reason to keep conversation history short.
Thedrummer has 3 models in our catalogue; the cheapest is Cydonia 24B V4.1 at 302 toman per thousand words and the dearest Skyfall 36B V2 at 509. Among the less common parameters it accepts logit_bias, logprobs, repetition_penalty, top_k, top_logprobs — all through the standard request body. It does not support include_reasoning, reasoning, which most models here do, so test before switching if your code relies on them. By context size the nearest option from another provider is Qwen3.8 2.4T A95B (batch) at 1,010,000 tokens.
Good fits: high-volume work such as classification, tagging and bulk summarising, agents that reach out to APIs and databases, extracting data against a fixed schema, analysing a long document or codebase in one request.
UnslopNemo v4.1 is the latest addition from the creator of Rocinante, designed for adventure writing and role-play scenarios.
Three real jobs, priced on this model
Each figure is derived from the prices above and moves when they do.
| Job | Tokens | Cost |
|---|---|---|
| One chat turn with a medium history | 1,500 in + 400 out | 220 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 534 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 16,247 toman |
Frequently asked
- How do I call UnslopNemo 12B from Iran?
- Sign up with your mobile number, top the wallet up in toman, create an API key, then in the official OpenAI SDK point base_url at https://api.uttapen.ir/v1 and set model to "thedrummer/unslopnemo-12b". Nothing else in your code changes.
- What does UnslopNemo 12B cost in toman?
- 116,050 toman per 1M input tokens and 116,050 toman per 1M output tokens; a 1,000-word request is around 302 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does UnslopNemo 12B take?
- Up to 1,024,000 tokens per request, roughly 768k words. A single answer can reach 819,200 tokens.
- Does UnslopNemo 12B support streaming and tool calling?
- Streaming (stream=true) works on every model here. This one supports tool calling in the standard OpenAI shape. Structured output through response_format works too.