*Decision Index leaderboard, Full score, 12 November 2026.*
A multimodal decision model: given a state (a web page and its screenshot, a document, a conversation: text, JSON
and images) and typed questions about it, it returns a probability for every option of every question in one forward
pass, without generating text.
Fine-tuned from [google/gemma-4-31B-it](https://huggingface.co/google/gemma-4-31B-it), with a linear readout over the
options.
- **Parameters:** 31.3B in bf16, plus a 255 × 5,376 readout in fp32
- **Input:** multimodal, text and images (a screenshot at `state.viewport_screenshot`, or data URLs in `images`)
- **Questions:** `choice` (up to 255 options), `noul` (true or false), `score` (a level on a scale)
- **Context:** 32,768 tokens per sequence; a longer request is split by questions, each part with the full state
- **Interfaces:** a Python API and an HTTP server in the System One format (`POST /v1/systemone`)
- **Licence:** [MachinePulse Community License](LICENSE): commercial use is allowed; commercial products and services
offered to third parties must show "Powered by karpo-decision (MachinePulse)"; production use for commercial
purposes by an entity whose annual revenue, with its affiliates, exceeds US$10M needs a commercial agreement.
It applies to the weights in this repository, including the current ones, from November 12, 2026
## Results
### Decision Index leaderboard
The [board](https://huggingface.co/spaces/multimodalart/jev-decision-index) ranks by the Full score, which its
maintainers measure on private tests only: 60% tests of the same skills as the public suite and 40% tasks from new
domains.
| Decision Index 0.4.1, board of 12 November 2026 | karpo-decision-31B |
|---|---|
| **Full score** | **73.9**, rank **#1**, the highest of 300 entries |
| Private tests, same skills (on the public scale) | 70.7 |
| Private tasks, new domains (on the public scale) | 78.6 |
| Public index (our run, adopted by the board) | 75.0 |
| Median latency (one GPU, one request at a time) | 94 ms per request |
| Calibration error | 4.8 points |
The board gives one rank to models within 0.9 points of the first model in a group: karpo-decision-31B (73.9) and
GLiDE 27B (73.4) share #1.
### Decision Index public suite
Our run of the official kit: 140,178 scored requests, 11 unsupported (a question over 32,768 tokens with its state).
Results: [runs/karpo-decision-31B](https://huggingface.co/datasets/MachinePulseAI/karpo-decision-31B-decision-index/tree/main/runs/karpo-decision-31B).
| | score |
|---|---|
| **Public index** (chance-corrected) | **75.0** |
| Raw index | 80.9 |
| Breadth | 74.7 |
| Knowledge & Reasoning | 65.5 |
| Language Understanding | 76.8 |
| Retrieval & Classification | 76.4 |
| Tools & Automation | 88.4 |
| Arts & Human Taste | 68.2 |
## The Karpo Decision family
*Score vs. size on the Decision Index 0.3 public suite, board of 12 November 2026.*
| Model | Base | Parameters |
|---|---|---|
| **karpo-decision-31B** | Gemma 4 31B | 31.3B |
| [karpo-decision-12B](https://huggingface.co/MachinePulseAI/karpo-decision-12B) | Gemma 4 12B | 12.0B |
| [karpo-decision-9B](https://huggingface.co/MachinePulseAI/karpo-decision-9B) | Qwen3.5 9B | 8.4B |
| [karpo-decision-4B](https://huggingface.co/MachinePulseAI/karpo-decision-4B) | Qwen3.5 4B | 4.5B |
| [karpo-decision-2B](https://huggingface.co/MachinePulseAI/karpo-decision-2B) | Qwen3.5 2B | 2.2B |
| [karpo-decision-0.8B](https://huggingface.co/MachinePulseAI/karpo-decision-0.8B) | Qwen3.5 0.8B | 0.85B |
## How it works
- **A readout, not generation.** Every option is labelled with an option code. At the `Answer: (` slot that ends a
question's branch, a linear readout scores 255 option codes and a softmax over the question's own options gives the
probabilities. Nothing is decoded, so the answer is always one of the options.
- **Many questions, one forward pass.** A request is one state and any number of questions, encoded as one sequence:
the list of questions, the state, then one branch per question with its options.
- **Branch attention.** A branch reads the shared block (questions and state) and itself, never another branch. The
state is computed once per sequence, and no question sees another question's options.
The question-list-first layout follows [FlexDM](https://github.com/1000luca/FlexDM) and
[jev-brain](https://github.com/wcole3/jev-brain); the shared-block and branch rule follows
[Sieve-31B-v3](https://huggingface.co/sthanika-ai/Sieve-31B-v3).
## Use
Inference code: [github.com/machinepulse-ai/karpo-decision](https://github.com/machinepulse-ai/karpo-decision). Python
3.12 or later and one GPU; the weights take 62.5 GB, long requests more. Loading the checkpoint as a plain chat model
does not reproduce its answers.
```bash
pip install "karpo-decision @ git+https://github.com/machinepulse-ai/karpo-decision"
```
```python
from huggingface_hub import snapshot_download
from karpo_decision.decider import Decider
path = snapshot_download("MachinePulseAI/karpo-decision-31B")
decider = Decider.from_pretrained(path, device="cuda")
response = decider.decide({
"state": "Order 1182: the customer asks to return a blender bought 45 days ago. Policy: returns within 30 days.",
"questions": {
"eligible": {"type": "noul", "instructions": "Is the return eligible under the policy?"},
"action": {"type": "choice", "instructions": "What should the agent do?",
"criteria": {"refund": "Issue a full refund", "decline": "Politely decline the return",
"escalate": "Escalate to a supervisor"}},
},
})
print(response["answers"])
# {"eligible": {"type": "noul", "noul": P(true)},
# "action": {"type": "choice", "choice":