How do I call ricursiveAI/Ripple-65B-Preview 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 "ricursiveai/ripple-65b-preview". Nothing else in your code changes.

What does ricursiveAI/Ripple-65B-Preview cost in toman?

69,244 toman per 1M input tokens and 207,732 toman per 1M output tokens; a 1,000-word request is around 360 toman. You pay for the usage that request actually reported, and a failed request costs nothing.

How much input does ricursiveAI/Ripple-65B-Preview take?

Up to 1,048,576 tokens per request, roughly 786k words. A single answer can reach 131,072 tokens.

Does ricursiveAI/Ripple-65B-Preview 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.

ricursiveAI/Ripple-65B-Preview API: toman pricing and code

ricursiveai/ripple-65b-preview

Tool callingJSON output

Create a key Try it

Input · per 1M tokens

69,244 toman

Output · per 1M tokens

207,732 toman

One 1,000-word request ≈

360 toman

You are billed for the usage the request actually reported. Prices follow the market. Cached input: 17,311 toman per 1M tokens.Pricing and top-ups

ricursiveAI/Ripple-65B-Preview 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.

PythonNode.jscurl

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="ricursiveai/ripple-65b-preview",
    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: "ricursiveai/ripple-65b-preview",
  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": "ricursiveai/ripple-65b-preview",
    "messages": [{"role": "user", "content": "Classify the ticket and give it a priority from 1 to 5."}],
    "response_format": {"type": "json_object"}
  }'

What is ricursiveAI/Ripple-65B-Preview good for?

ricursiveAI/Ripple-65B-Preview is one of Ricursiveai's models. Put "ricursiveai/ripple-65b-preview" in the model field and the rest of your code stays as it is. ricursiveAI/Ripple-65B-Preview keeps 1,048,576 tokens in view at once, and that number is what caps the conversation history in your product. A single response can run to 131,072 tokens. On price it sits in the "cheap" band — cheaper than 282 and dearer than 103 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 69,244 toman per 1M input tokens and 207,732 per 1M output tokens. A 1,000-word round trip on ricursiveAI/Ripple-65B-Preview lands near 360 toman. It supports cached input: repeated context is billed at 17,311 toman per 1M, which matters a lot if your system prompt is long. 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 Command R (08-2024): ricursiveAI/Ripple-65B-Preview works out about 10% 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 278 thousand-word requests on ricursiveAI/Ripple-65B-Preview, and every 1,000 toman is about 2,778 words of round trip. A job with one million input tokens and one million output tokens comes to 276,975 toman in total. Filling this model's 1,048,576-token window costs 72,607 toman on the input side alone, which is the real reason to keep conversation history short.

Among the less common parameters it accepts logprobs, top_logprobs — all through the standard request body. It does not support include_reasoning, reasoning, structured_outputs, 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 DeepSeek V4 Flash 0423 at 1,048,576 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.

Provider's own description

Ripple-65B-Preview by ricursiveAI, a 65B model with native tool calling, served in BF16.

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	187 toman
Summarising a ten-page document	4,000 in + 600 out	402 toman
Classifying a thousand short rows	120,000 in + 20,000 out	12,464 toman

Job

Tokens

Cost

One chat turn with a medium history

1,500 in + 400 out

187 toman

Summarising a ten-page document

4,000 in + 600 out

402 toman

Classifying a thousand short rows

120,000 in + 20,000 out

12,464 toman

Frequently asked

How do I call ricursiveAI/Ripple-65B-Preview 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 "ricursiveai/ripple-65b-preview". Nothing else in your code changes.
What does ricursiveAI/Ripple-65B-Preview cost in toman?: 69,244 toman per 1M input tokens and 207,732 toman per 1M output tokens; a 1,000-word request is around 360 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does ricursiveAI/Ripple-65B-Preview take?: Up to 1,048,576 tokens per request, roughly 786k words. A single answer can reach 131,072 tokens.
Does ricursiveAI/Ripple-65B-Preview 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.