uttapen

LFM2.5-2.6B (free) API: toman pricing and code

liquid/lfm-2.5-2.6b:free

Free · shared capacitytoolsreasoningjson
Input · per 1M tokens
0 toman
Output · per 1M tokens
0 toman
One 1,000-word request ≈
0 toman

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

LFM2.5-2.6B (free) 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="liquid/lfm-2.5-2.6b:free",
    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 LFM2.5-2.6B (free) good for?

LFM2.5-2.6B (free) comes from Liquid; in uttapen you reach it with the model id "liquid/lfm-2.5-2.6b:free". It accepts up to 65,536 tokens of input per call, so a long document or several source files fit in a single request. A single response can run to 8,192 tokens. Using it costs nothing. In exchange the capacity is shared, so during busy hours a request can come back empty-handed.

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; it has a reasoning mode that pays off on multi-step problems, maths and debugging. All of it works through the standard parameters of the official OpenAI SDK — no custom client, no wrapper. Keep in mind that reasoning tokens are output tokens and do appear on the bill.

Pricing is 0 toman per 1M input tokens and 0 per 1M output tokens. A 1,000-word round trip on LFM2.5-2.6B (free) lands near 0 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 North Mini Code (free), and its context window is smaller. Both run on the same key and the same code, so trying the other one is a single string change.

Among the less common parameters it accepts logprobs, max_completion_tokens, min_p, repetition_penalty, top_k, top_logprobs — all through the standard request body. By context size the nearest option from another provider is Nano Banana Pro (Gemini 3 Pro Image Preview) at 65,536 tokens.

Good fits: proving an idea works before you spend anything, logic puzzles and code review, agents that reach out to APIs and databases, extracting data against a fixed schema.

Provider's own description

LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for agentic coding or...

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 out0 toman
Summarising a ten-page document4,000 in + 600 out0 toman
Classifying a thousand short rows120,000 in + 20,000 out0 toman

Frequently asked

How do I call LFM2.5-2.6B (free) 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 "liquid/lfm-2.5-2.6b:free". Nothing else in your code changes.
What does LFM2.5-2.6B (free) cost in toman?
0 toman per 1M input tokens and 0 toman per 1M output tokens; a 1,000-word request is around 0 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does LFM2.5-2.6B (free) take?
Up to 65,536 tokens per request, roughly 49k words. A single answer can reach 8,192 tokens.
Does LFM2.5-2.6B (free) 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.
What are the limits on a free model?
Free models have a daily per-user cap and their capacity is shared with everyone else. When the shared pool is exhausted the request is refused with a clear error and your wallet is untouched.