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Hermes 3 70B Instruct API: toman pricing and code

nousresearch/hermes-3-llama-3.1-70b

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Input · per 1M tokens
203,088 toman
Output · per 1M tokens
203,088 toman
One 1,000-word request ≈
528 toman

You are billed for the usage the request actually reported. Prices follow the market.Pricing and top-ups

Hermes 3 70B Instruct 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="nousresearch/hermes-3-llama-3.1-70b",
    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))

What is Hermes 3 70B Instruct good for?

Hermes 3 70B Instruct is one of Nous Research's models. Put "nousresearch/hermes-3-llama-3.1-70b" in the model field and the rest of your code stays as it is. Hermes 3 70B Instruct keeps 131,072 tokens in view at once, and that number is what caps the conversation history in your product. A single response can run to 16,384 tokens. On price it sits in the "cheap" band — cheaper than 112 and dearer than 294 of the other paid models in the catalogue.

What you get on top of text in, text out: 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.

Input runs at 203,088 toman per 1M tokens and output at 203,088 — output costs 1× input, so trimming the answer saves more than trimming the prompt. 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 Gemma 2 27B: Hermes 3 70B Instruct works out roughly 1.1× 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 189 thousand-word requests on Hermes 3 70B Instruct, and every 1,000 toman is about 1,894 words of round trip. A job with one million input tokens and one million output tokens comes to 406,175 toman in total. Filling this model's 131,072-token window costs 26,619 toman on the input side alone, which is the real reason to keep conversation history short.

Its nearest relative in the catalogue is "nousresearch/hermes-3-llama-3.1-405b", and choosing between those two is where most people hesitate. On a thousand-word request this variant works out 1.4× cheaper (528 against 754 toman).

Nous Research has 4 models in our catalogue; the cheapest is Hermes 4 70B at 200 toman per thousand words and the dearest Hermes 4 405B at 1,509. Among the less common parameters it accepts logit_bias, min_p, repetition_penalty, top_k — all through the standard request body. It does not support include_reasoning, reasoning, tool_choice, tools, 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 Aion-2.0 at 131,072 tokens.

Where it makes sense: high-volume work such as classification, tagging and bulk summarising, extracting data against a fixed schema.

Provider's own description

Hermes 3 is a generalist language model with many improvements over [Hermes 2](/models/nousresearch/nous-hermes-2-mistral-7b-dpo), including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence, and improvements across the...

Three real jobs, priced on this model

Each figure is derived from the prices above and moves when they do.

JobTokensCost
One chat turn with a medium history1,500 in + 400 out386 toman
Summarising a ten-page document4,000 in + 600 out934 toman
Classifying a thousand short rows120,000 in + 20,000 out28,432 toman

Frequently asked

How do I call Hermes 3 70B Instruct 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 "nousresearch/hermes-3-llama-3.1-70b". Nothing else in your code changes.
What does Hermes 3 70B Instruct cost in toman?
203,088 toman per 1M input tokens and 203,088 toman per 1M output tokens; a 1,000-word request is around 528 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does Hermes 3 70B Instruct take?
Up to 131,072 tokens per request, roughly 98k words. A single answer can reach 16,384 tokens.
Can I stream Hermes 3 70B Instruct's output?
Yes — with stream=true you get SSE events as the tokens are produced. This model has no tool calling and no image input, so pick a different one if you need either.