Blame for README.md

---
tags:
- decision-model
- situated-world-model
- agents
- robotics
- world-model
- api
library_name: custom
pipeline_tag: text-classification
license: other
license_name: proprietary
license_link: https://machinefi.com/terms-of-service
---

<p align="center">
  <img src="banner.svg" alt="Trio-Spark — Fast judgment for the next move" width="100%">
</p>

# Trio-Spark

**Current release: Trio-Spark v1.4 · October 28, 2026**

Trio-Spark is MachineFi's hosted **Situated World Model** for bounded decisions. Give it the current state and 2–8 allowed actions. One pass returns a selected action and a probability for every option, with no free-form answer to parse.

**This repository is a model card for the commercial API. Model weights and training code are not distributed here.**

[Try the playground](https://platform.machinefi.com/spark) · [Get an API key](https://platform.machinefi.com/login?callback=%2Fspark) · [API docs](https://machinefi.com/docs) · [Pricing](https://machinefi.com/pricing) · [Demos and clients](https://github.com/machinefi/trio-spark) · [v1.4 release post](https://machinefi.com/blog/trio-spark-v14-decisions)

## What it does

```text
environment signals → current state → Trio-Spark → selected action → executor
                            ↑                              │
                            └──────── fresh feedback ──────┘
```

Your application supplies the state, legal actions, executor and safety controls. Spark handles the bounded judgment step: routing, tool selection, GUI actions, game moves, robot skills and operational decisions.

Input can be structured text or JSON, one image or camera frame, or a 2–4-frame sampled video window. In v1.4 one model serves text, images and video. The API accepts 2–8 choices and at most 1,024 expanded input tokens, including task, state, choices and any visual input.

## API quickstart

Sign in to the [Trio-Spark console](https://platform.machinefi.com/login?callback=%2Fspark), select **API Keys**, and create a key. Set it as `TRIO_SPARK_API_KEY` in your environment.

```bash
curl https://platform.machinefi.com/api/spark/v1/decisions \
  -H "Authorization: Bearer $TRIO_SPARK_API_KEY" \
  -H "Content-Type: application/json" \
  -H "Idempotency-Key: $(uuidgen)" \
  -d '{
    "model": "trio-spark",
    "task": "The user asked to export the current report as CSV. Choose the next safe UI action from the available controls.",
    "state": {
      "app": "Reports",
      "screen": "Report details",
      "visible_controls": ["Export menu", "Filters", "Help"]
    },
    "choices": [
      {"id": "open_export_menu", "description": "Open the Export menu"},
      {"id": "open_filters", "description": "Open report filters"},
      {"id": "wait", "description": "Wait for more information"}
    ]
  }'
```

Use `choice_id` to identify the selection. The response includes the complete probability distribution, confidence, a `decide`, `review` or `abstain` disposition, usage and latency. Reuse the same idempotency key and identical request body when retrying an uncertain request.

Use the model ID **`trio-spark`**. It always runs the current release, and each response reports the exact release in `model_version`. Earlier identifiers (`trio-spark-preview`, `trio-spark-v1.0` to `trio-spark-v1.3`) remain accepted and route to the current model; they do not pin historical weights. The [API docs](https://machinefi.com/docs) cover visual requests, errors, limits and the full response schema.

## Benchmarks

Trio-Spark v1.4 against three other fast decision models, on the same items for every model. Scores are accuracy percentages; the best score in each row is bold. Trio-Spark is best or tied for best on seven of thirteen.

| Benchmark (items) | Trio-Spark | Jev 1.14 | Clef-Flash | Clef |
| --- | ---: | ---: | ---: | ---: |
| AG News (300) | **90.7** | 82.7 | 88.7 | 87.0 |
| SST-2 (300) | **96.3** | 95.3 | **96.3** | 94.3 |
| TweetEval offensive (300) | **87.0** | 84.3 | 84.3 | 82.7 |
| Banking77 (77-way)† (300) | 88.2 | 80.1 | **94.7** | 94.6 |
| RTE (277) | **92.8** | 91.3 | 91.0 | 91.7 |
| SNLI (150) | **88.7** | 76.0 | 82.7 | 82.7 |
| PubMedQA (300) | **82.7** | 76.7 | 79.7 | 77.7 |
| BoolQ (300) | 91.7 | 90.3 | 91.7 | **92.7** |
| HelpSteer2 (0–4 score) (300) | **44.3** | 38.9 | 42.7 | 41.3 |
| ARC-Easy (300) | 97.0 | **99.7** | **99.7** | **99.7** |
| HellaSwag (300) | 94.7 | 94.7 | **98.7** | 98.0 |
| PIQA (300) | 93.0 | **95.7** | 90.3 | 91.0 |
| WinoGrande (300) | 89.7 | 89.3 | **98.0** | 93.7 |

Method and limitations:

- Developer-run evaluation on the listed samples, not full-dataset or independently certified leaderboard scores. Trio-Spark was evaluated through the production API code path, one request per item; requests rejected by the input limit or content filter count as wrong.
- Jev 1.14 through its official API on October 28, 2026; Clef and Clef-Flash recorded October 7–8, 2026. HelpSteer2 and Banking77 peer scores average five orderings of the options.
- † Banking77 has 77 choices and was read out offline from the same weights; the public API accepts at most 8 choices per request.
- These numbers measure text decisions. They do not establish image, video, GUI-control or real-world task performance.

The [release post](https://machinefi.com/blog/trio-spark-v14-decisions) has the full protocol, and the [downloadable results](https://machinefi.com/spark/benchmarks/v14-launch-table-2026-10-28.json) include every count.

## Releases

- **v1.4 · October 28, 2026 (current).** One model for text, images and video; served as `trio-spark`.
- **v1.3 · October 15, 2026.** Text decision update.
- **v1.0 · September 30, 2026.** First release, with replayable [drone, browser and robot-arm demos](https://github.com/machinefi/trio-spark).

## Limitations and intended use

Evaluate Spark on your own screens, frames and actions before increasing automation. Latency depends on the request and workload; nothing on this card is a latency guarantee.

Spark selects among supplied choices. It does not execute actions, operate a browser by itself, predict future frames, or provide general conversational answers. Include choices such as **wait** or **ask for review** when appropriate.

Applications remain responsible for permissions, legal-action filtering, hard safety rules, human confirmation for consequential actions, execution safeguards and fallback behavior. A high model probability is not a guarantee of correctness.

## Access and licensing

The hosted API is a commercial service subject to [MachineFi's terms](https://machinefi.com/terms-of-service). Text and visual input cost **$0.042 per million billed input tokens**; output is free. New accounts receive 100 free decisions. See [pricing](https://machinefi.com/pricing) for current details.

The [public Trio-Spark repository](https://github.com/machinefi/trio-spark) contains Apache-2.0 clients and demo integrations. That code license does not grant access to model weights or training artifacts. This Hugging Face repository does not provide downloadable weights or a local-inference package.

Research weights: [MachineFi/Trio-Spark-DI-1.4](https://huggingface.co/MachineFi/Trio-Spark-DI-1.4) is a text-only Q8_0 build of the v1.4 model the API serves, released under CC BY-NC 4.0 for research and evaluation.