Ling 3.0 Flash Sante (free) API: toman pricing and code
inclusionai/ling-3.0-flash-sante:free
Free · shared capacitytoolsreasoningYou are billed for the usage the request actually reported. Prices follow the market.Pricing and top-ups
Ling 3.0 Flash Sante (free) example: a multi-step problem with reasoning
The example is picked from this model's own capabilities. Drop in your key and it runs as is.
from openai import OpenAI
client = OpenAI(base_url="https://api.uttapen.ir/v1", api_key="sk-up-…")
resp = client.chat.completions.create(
model="inclusionai/ling-3.0-flash-sante:free",
messages=[{"role": "user", "content": (
"A shop has 3 warehouses. A ships 120 orders a day, B ships 85 and C ships 40. "
"If C closes and its load is split between A and B in proportion to their capacity, how many does each ship a day? "
"Work through it step by step and give just the two numbers at the end."
)}],
reasoning_effort="medium", # low | medium | high
)
print(resp.choices[0].message.content)
# reasoning tokens count as output tokens too:
print(resp.usage.completion_tokens_details)curl https://api.uttapen.ir/v1/chat/completions \
-H "Authorization: Bearer sk-up-…" \
-H "Content-Type: application/json" \
-d '{
"model": "inclusionai/ling-3.0-flash-sante:free",
"messages": [{"role": "user", "content": "120 and 85 daily orders split across two warehouses; work through it step by step."}],
"reasoning": {"effort": "medium"}
}'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: "inclusionai/ling-3.0-flash-sante:free",
messages: [{ role: "user", content: "120 and 85 daily orders are split between two warehouses; work through it step by step and give just the two numbers at the end." }],
reasoning_effort: "medium",
});
console.log(resp.choices[0].message.content);
console.log(resp.usage.completion_tokens_details);What is Ling 3.0 Flash Sante (free) good for?
inclusionAI publishes this model; we expose it under the id "inclusionai/ling-3.0-flash-sante:free". Its context window is 262,144 tokens, roughly 197k English words in one request. A single response can run to 32,768 tokens. It is free: nothing leaves your wallet. The capacity is shared across all users and there is a daily cap per account, so treat it as a testing lane rather than a production dependency.
Capabilities available on this id: it supports tool calling, so it can invoke your own functions with valid arguments; 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.
For a back-of-envelope figure: about 0 toman per 1,000-word exchange (0 in, 0 out, per 1M tokens). 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 larger. Both run on the same key and the same code, so trying the other one is a single string change.
Its nearest relative in the catalogue is "inclusionai/ling-3.0-flash-fin:free", and choosing between those two is where most people hesitate.
inclusionAI has 4 models in our catalogue; the cheapest is Ling 3.0 Flash at 32 toman per thousand words and the dearest Ling 3.0 Flash Fin at 91. Among the less common parameters it accepts logprobs, repetition_penalty, top_k, top_logprobs — all through the standard request body. It does not support response_format, 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 Trinity Large Thinking at 262,144 tokens.
What to use it for: proving an idea works before you spend anything, logic puzzles and code review, agents that reach out to APIs and databases, analysing a long document or codebase in one request.
Ling 3.0 Flash Sante is a health and medicine-focused mixture-of-experts model from InclusionAI, built on Ling 3.0 Flash with 5.1B active parameters out of 124B total. It is designed for...
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 | 0 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 0 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 0 toman |
Frequently asked
- How do I call Ling 3.0 Flash Sante (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 "inclusionai/ling-3.0-flash-sante:free". Nothing else in your code changes.
- What does Ling 3.0 Flash Sante (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 Ling 3.0 Flash Sante (free) take?
- Up to 262,144 tokens per request, roughly 197k words. A single answer can reach 32,768 tokens.
- Does Ling 3.0 Flash Sante (free) support streaming and tool calling?
- Streaming (stream=true) works on every model here. This one supports tool calling in the standard OpenAI shape.
- 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.