Ethical Stack.

HunyuanImage 3.0

80B native multimodal image-generation model with 13B active parameters; supports text-to-image and separate Instruct image-editing releases.

Score calculation

(3 + 2 + 5 + 1 + 8) ÷ 5 = 3.8

5 of six dimensions rated. Unrated dimensions are excluded from the average.

Full scoring method ↗
Setup details

HunyuanImage-3.0 base text-to-image checkpoint under Tencent Hunyuan Community License; Instruct/edit checkpoint is a separate release.

What fits your needs

HunyuanImage-3.0 base text-to-image checkpoint under Tencent Hunyuan Community License; Instruct/edit checkpoint is a separate release.

Text to image

Official model page documents a native multimodal text-to-image checkpoint and links separate Instruct image-editing weights.

See the evidence

Local pipeline

The official card provides Transformers loading and a local demo with image-size and model parameters.

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Large model

The model card states 80B total parameters with 13B active per token, and names CUDA 12.8 setup.

See the evidence
Tradeoffs to expect

Territorial license limits

Tencent Community License excludes EU, UK and South Korea and includes other distribution and use conditions; do not treat as an unrestricted global release.

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Optional cloud enhancement

Prompt enhancement in the demo can require a Tencent Cloud API key; it is optional and the base pretrain checkpoint does not rewrite prompts automatically.

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How to switch

Start locally

Download the checkpoint and run Tencent’s repository instructions with compatible Python/CUDA; opt into prompt enhancement only if needed.

See the evidence
Practical questions

License territory

The model license excludes use, reproduction, modification, distribution or display in the EU, UK and South Korea.

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Minors and impersonation

The license acceptable-use policy prohibits exploiting or harming minors and impersonating another person without consent, authorization or legal right.

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Hosted route

Any hosted inference provider adds its own prompt handling and location terms; weights alone don’t show a service privacy policy.

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Energy practices

3/10↑

This grades disclosed operating practices, not the electricity or emissions of a particular generation.

See the evidence

The release gives limited runtime or control details but no comparable per-task footprint or electricity-source evidence. Tencent documents CUDA 12.8, Python 3.12+ and local device-map execution as the stated runtime boundary. The image demo supports image-size selection and an optional FlashInfer MoE implementation for faster inference; the card does not quantify its energy or resource savings.

1 + 1 reporting + 0 electricity + 1 controls = 3/10. This grades documented practices and transparency.

Per-task energy, serving region, facility electricity mix, water and independent footprint review are not established in the cited release sources.

Reporting1/3
Tencent documents CUDA 12.8, Python 3.12+ and local device-map execution as the stated runtime boundary.
Electricity sourcing0/3
The release materials do not report matched regional electricity sourcing or carbon-free supply for training or inference.
Resource controls1/3
The image demo supports image-size selection and an optional FlashInfer MoE implementation for faster inference; the card does not quantify its energy or resource savings.

Water disclosure

Water reporting has not been assessed for this choice.

Training data

2/10↑

The model release does not provide a complete inspectable training-source permission record.

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The reviewed release documentation the release reports curated data and post-training but does not name a training source inventory or rights basis. It provides no source-level permission ledger or creator remedy; a model-weight license governs downstream use, not the material used to train the model.

1 base + 1 source transparency + 0 documented permission + 0 creator controls = 2/10.

Named source inventory, source-level licenses, creator remedies, and independent verification remain unestablished for this release.

Source transparency1/3
The release reports curated data and post-training but does not name a training source inventory or rights basis.
Documented permission0/4
The release sources do not publish a training-source permission basis or rights ledger; the weight license doesn’t settle training-data permission.
Creator controls0/2
No training-source creator permission-before-use, opt-out, removal or retraining route is documented for this release.
Data-rights rubric ↗

Your data & privacy

—Not enough evidence↑

Privacy has no single score for these downloadable weights because handling depends on the inference host and integrations.

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The release can be run locally, but it also appears in hosted provider routes; those operators set their own request retention, training and region terms. A cloud API, where offered, is a separate policy route and is not inherited from the local weights.

A selected host, network path, telemetry, logging, external prompt enhancement, and data retention need route-specific review.

Openness

5/10↑

Weights and inference code are public under Tencent’s Community License, which has territorial and use restrictions.

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Tencent publishes the model weights, inference code and technical report; its community license limits territory and usage. The training data is not fully reproducible from the release. This rating concerns release artifacts and reproducibility, not training-data permission.

5/10 reflects public weights and inference code, offset by the restricted community license and incomplete training reproducibility.

Exact training sources, source permissions and a complete training recipe remain unavailable.

Worker protections

1/10↑

No model-specific worker safeguards are established for Tencent in the reviewed model sources.

See the evidence

The model release pages describe weights and technical properties, not conditions for employees, data annotators, evaluators, moderators, or infrastructure contractors. This is a source-bounded disclosure gap, not evidence of mistreatment. These findings concern the developer or operator. This product’s use in a particular deployment needs separate evidence.

1 base + 0 conditions + 0 worker voice/remedy + 0 evidence/follow-through = 1/10; this is a disclosure finding, not proof of abuse.

Worker locations, pay and conditions, supplier coverage, voice mechanisms, labor audits, and remediation outcomes are not established by these model-release sources.

Pay & conditions0/3
No worker-level conditions or supply-chain safeguards are established in this model-family source set. This is a disclosure gap, not proof of mistreatment.
Worker voice & remedy0/3
The model sources do not document a worker voice or remedy mechanism for data, evaluation, or infrastructure labor.
Evidence & follow-through0/3
No independent worker-level audit or remediation outcome is established in the reviewed model sources.
Workers rubric ↗

Military ties

8/10Not established↑

This finding concerns binding use restrictions on the named release, not proof of how any user deploys it.

See the evidence

The binding license prohibits military-purpose use, but doesn’t spell out a broad prohibition on weapons, surveillance or military-intelligence applications; enforcement outcomes are not documented. The reviewed release sources do not document product-specific enforcement outcomes.

7 base + 1 safeguard adjustment = 8/10 (3 of 9 safeguard points; every 3 adds 1). No military relationship was established in the cited sources. This ranks above known defense ties without claiming a verified clean record.

Actual deployments, end users and independent enforcement outcomes are not established by the cited model-release sources.

Use restrictions3/4
The binding license prohibits military-purpose use, but doesn’t spell out a broad prohibition on weapons, surveillance or military-intelligence applications; enforcement outcomes are not documented.
Enforcement & oversight0/3
No military-specific review, enforcement or remedy results are documented in the model release materials.
Relationship disclosure0/2
The release documents license terms but no product-specific government or defense deployment.

Release-specific source review found no qualifying model deployment evidence.

Military rubric ↗

BDS targets

Not listed↑

Tencent is not named in the two official BNC campaign lists checked. This is a limited list check, not BDS approval.

See the evidence

The official BNC consumer boycott/pressure guide and No Tech campaign page do not name Tencent among their current targets. BDS uses selective campaigns, so absence from these lists is neutral and should not be read as a clean record or approval. These findings concern the developer or operator. This product’s use in a particular deployment needs separate evidence.

This check covers only named targets in the two cited BNC campaigns; it does not cover all BDS campaigns, local groups, investments, suppliers, or downstream hosts. Lists and ownership may change.

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