README.md

---
language:
- ja
- en
license: other
license_name: openmdw-1.1
license_link: https://openmdw.ai/license/1-1/
library_name: cosmos
base_model: nvidia/Cosmos3-Edge
base_model_relation: finetune
tags:
- physical-ai
- viewpoint-planning
- uav
- research
- cosmos3
---

# Tancho Generator — router v5 research release

**A reproducible research baseline for generating numeric observation viewpoints.** Developed in Japan by Vox, Tokyo; compute provided by Nebius AI Cloud. Released September 14, 2026.

This release contains **two fine-tuned checkpoints and a deterministic input-based router**. “v5” is the routing-policy version, not a fifth checkpoint or the upstream model version. It is the current adopted Tancho research baseline. The older [Tancho release](https://huggingface.co/v13s/tancho) contains different weights and a different output protocol; its 21/40 result is not this release's metric.

## What it does

Given a reference image and trusted numeric context (current/target coordinates, target size, required pixels, viewing direction, approved volume, speed and mission-time limits), the Generator emits a JSON list:

```json
[{"offset_m": [0.0, 20.0, 15.0], "dwell_ms": 2000, "speed_mps": 3.0}]
```

This is a **format illustration**, not a certified plan. `offset_m` is the displacement from the target in local ENU metres; add the target position to obtain the viewpoint. The other fields are dwell milliseconds and outbound speed in m/s. A separate validator checks the unchanged answer.

This application Generator uses Cosmos's **autoregressive tower**. It does not train the application's Reasoner role (deciding what to observe), use the diffusion tower to produce a continuous camera trajectory, or execute flight control. The intended architecture remains observation objective → viewpoint sequence → detailed camera/aircraft trajectory → flight control.

## Exactly what is released

| Component | Path | Role |
|---|---|---|
| mixed240 | `checkpoints/mixed240/` | Default viewpoint generation |
| balanced288 | `checkpoints/balanced288/` | Eligible stationary observations only |
| router v5 | `tancho/viewpoint_router.py` | Select once before inference |
| validators and pinned-backend helpers | `tancho/`, `training/`, `run_request.py` | Preserve raw output and check geometry |
| saved-output evidence | `evidence/` | Re-score the reported v5 answers without new inference |

Each checkpoint is the original 31-file retained export (4,905,905,551 bytes), including the fine-tuned AR tower and frozen vision encoder. The two exports total 9,811,811,102 bytes before code and documentation. Framework configuration/assets in the exports do not mean diffusion/VAE weights were fine-tuned or that the export alone is a full Cosmos multimodal snapshot. Loading uses the pinned Cosmos Framework and base-overlay procedure in [REPRODUCE.md](REPRODUCE.md), **not a plain `transformers.from_pretrained` call or an HF-hosted inference endpoint**.

Router eligibility requires all of:

- Remaining mission time after return margin is exactly 1, 2, or 3 seconds.
- Trusted-input preflight is undetermined rather than an established invalid/infeasible request.
- Conversion of the current position to relative coordinates and back is exact.
- A current-position, 1000 ms stationary validation probe passes every check.

Eligible inputs use balanced288 with an explicit current-relative-position input. All other inputs use mixed240 and the original relative-coordinate prompt. The probe is only an eligibility check; it is not returned as a model answer. There is one generation per request, without answer repair, retry, or cross-model fallback. The **1/2/3 seconds describe remaining mission budget, not inference latency or flight-control frequency**. The included snapshot also contains older explicit policies and protocol helpers as dependencies; only `viewpoint-router-v5` is the advertised release. Neither move432 nor the experimental timing-input router is released here.

## Measured results and unresolved failures

Success means passing the contract and all evaluated numerical geometry/envelope checks together. These results are from the fixed v4-versus-v5 comparison on September 13, 2026.

| Evaluation group | Cases | v4 accepted | v5 accepted |
|---|---:|---:|---:|
| New stationary, 1-second budget | 64 | 56 | 60 |
| New stationary, 2-second budget | 64 | 53 | 60 |
| New stationary, 3-second budget | 64 | 53 | 60 |
| Previously evaluated stationary regression cases | 128 | 111 | 122 |
| Movement required | 64 | 15 | 15 |
| Normal numeric conditions | 224 | 221 | 221 |
| Current viewpoint valid, 4-second boundary | 32 | 0 | 0 |
| Current position on the wrong side | 32 | 0 | 0 |

New stationary success is **180/192 (93.75%)**, with 22 paired improvements and 4 regressions against v4. This is not overall accuracy. The 352 cases outside the stationary branch had identical raw outputs across policies. All 1,344 original generations and their input/model identities were audited; the original GPU and temporary disk were deleted. The adopted implementation passed 93 related CPU tests.

**The movement and boundary failures remain unresolved.** balanced288 had previously failed a broad deployment comparison due to movement regression; v5 adopts it only within the stationary branch. Later movement/timing experiments do not change these weights or results.

The 544 new numerical geometries were not in earlier packs; 128 cases are explicitly reused regression cases. Reference images reuse the existing evaluation split. Normal cases are 28 base scenes × 8 symmetry transformations, not 224 independent flights. Numerical geometry is synthetic and is not tied to reconstructed objects in the images. Camera scoring uses a fixed 3840-pixel width and 81-degree field of view. Passing does not establish image understanding, occlusion handling, actual image quality, field generalization, or flight safety. The evaluation informed adoption and is not an untouched external certification set.

## Training provenance

Both runs started independently from pinned pretrained `nvidia/Cosmos3-Edge` revision `a9d944e2c6a1bf9f48b92ad16348e70c5f1836ba`; neither continues the retired parent-40 fine-tune.

| Item | mixed240 | balanced288 |
|---|---|---|
| Training examples | 480 mixed numeric cases | 576 cases: 480 normal + 96 time-constrained |
| Epochs / updates | 4 / 240 | 4 / 288 |
| Learning rate / gradient accumulation | 1e-6 / 8 | 1e-6 / 8 |
| Evaluated retained export | Final 240-update export | Final 288-update export |

For each model, **233 AR tensors were trainable and 437 vision tensors were frozen**. Verification of 670 exported tensors is not a claim that all 670 were trained. Numerical teachers come from the project's geometry/planning code, not human-reviewed observation decisions. Training uses reference tiles from public GSI Omachi footage, with evaluation tiles separated within the same flight. The synthetic geometry varies independently of the reference imagery. See [SOURCES.md](SOURCES.md).

## Use and release verification

See [REPRODUCE.md](REPRODUCE.md) for download, CPU saved-answer rescoring, request preparation, and the pinned CUDA backend procedure. `smoke.py` re-scores 672 previously generated v5 answers; it makes **zero model calls** and does not measure fresh accuracy. Release verification checks exported bytes and downloaded package behavior; it does not add a new performance benchmark or a Jetson measurement.

Intended runtime is Jetson Orin NX 16GB, but latency, memory use with two checkpoints, and device deployment remain unmeasured. No learned-model real-flight execution has been validated. Upstream capabilities cannot be transferred into claims about this fine-tune.

## Licenses and attribution

Weights and upstream model artifacts retain [OpenMDW 1.1](licenses/LICENSE.OpenMDW-1.1). Original Vox code, documentation, and synthetic evaluation records are under [MIT](LICENSE-CODE); third-party terms remain applicable to their artifacts. [NOTICE.md](NOTICE.md) records scope and attribution. No source footage, extracted frames, client materials, credentials, or complete internal run archives are distributed. NVIDIA, Nebius, and GSI do not endorse this release.

Contact: tancho@vox.delivery