# We Open-Sourced a 322M Decision Model. Now Its API Is Free

> Source: <https://dev.to/montydrief/we-open-sourced-a-322m-decision-model-now-its-api-is-free-187e>
> Published: 2026-10-10 21:34:17+00:00

**Two days ago, we released THX-01, an open-source decision model that outperforms Jev on several benchmarks and can even run locally on a smartphone. Today, anyone can use it through our free API.**

Hi everyone! I'm Farid, Co-Founder of HAL-X AI.

A couple of days ago, our team open-sourced **THX-01**, a 322M-parameter multilingual decision model designed to make AI decision-making faster, cheaper, and more accessible.

Yesterday, we opened our hosted API to everyone. **No API key, no sign-up, and no payment required.**

And the response has been incredible!

Since launch, we've already processed:

We're excited to see developers experimenting with what a small, specialized decision model can do.

Most applications don't actually need an LLM to generate paragraphs of text.

Sometimes, you just need to answer a simple question:

Using a large generative model for these tasks can introduce unnecessary latency and cost.

**THX-01 takes a different approach.**

It's a non-autoregressive model that processes a document or message alongside typed questions and returns structured answers with calibrated probabilities in a single forward pass.

Approximately **10 milliseconds** on our benchmark hardware.

No token-by-token generation.

You can make your first request right now.

No authentication required.

```
curl https://api.hal-x.ai/v1/systemone \
  -H "Content-Type: application/json" \
  -d '{
    "state": "My card was charged twice for one order",
    "questions": {
      "team": {
        "type": "choice",
        "question": "Which team handles this?",
        "criteria": {
          "billing": "billing",
          "tech": "technical",
          "sales": "sales"
        }
      }
    }
  }'
```

THX-01 evaluates the available choices and returns the predicted decision with probabilities.

The API supports:

| Type | What it does | 
|---|---|
| Choice | Classification with probabilities | 
| Yes/No | Binary decisions | 
| Score | Ordered scoring | 
| Number | Extract exact numbers from documents | 
| Excerpt | Extract verbatim passages | 
| Citations | Identify supporting text | 

You can submit multiple questions in a single request.

**Full API documentation:** [https://api.hal-x.ai/docs/thx-01](https://api.hal-x.ai/docs/thx-01)

We benchmarked THX-01 against TypeSafe Jev 1.13 using 2,843 multilingual support tickets across four languages.

Here are the results:

| Metric | THX-01 | Jev 1.13 | 
|---|---|---|
| Accuracy | **98.4%** | 97.4% | 
| Calibration error | **0.003** | 0.007 | 
| Measured latency | **~10 ms** | 331 ms | 
| Open weights | Yes | No | 

THX-01 achieved higher accuracy and better calibration on this benchmark, with approximately 33x lower measured latency.

The latency measurements use different serving setups, so they're not a controlled hardware-to-hardware comparison.

We don't claim THX-01 outperforms Jev everywhere, but these results demonstrate how competitive specialized, lightweight decision models can be.

THX-01 contains just **322 million parameters**.

It was designed to support efficient inference without requiring a massive GPU infrastructure.

With a suitable runtime, it can even run locally on smartphones.

You can also install the Python package:

```
pip install thx01
```

The model supports 18 post-training languages, with particular attention to Azerbaijani and multilingual robustness.

We're releasing THX-01 under **Apache 2.0**, including its model weights, source code, and training scripts.

We believe developers should have the freedom to run, modify, deploy, and build on top of their AI models.

At HAL-X AI, our goal is to contribute to the global open-source AI ecosystem and make efficient AI accessible to more people.

That's also why we've made the hosted API free to use, subject to rate limits.

**Free API:** [https://api.hal-x.ai/docs/thx-01](https://api.hal-x.ai/docs/thx-01)

**Model weights and code:** [https://huggingface.co/doofz/THX-01](https://huggingface.co/doofz/THX-01)

**Interactive demo:** [https://huggingface.co/spaces/doofz/THX-01-demo](https://huggingface.co/spaces/doofz/THX-01-demo)

**Python package:**

```
pip install thx01
```

We're still improving THX-01, and we'd love to hear feedback from developers building AI agents, automation pipelines, document processing systems, and classification services.

If you build something using THX-01, we'd love to see it!