Model
DeepSeek-V3
Publisher
DeepSeek (China)
Licence
DeepSeek License Agreement, Version 1.0
You partially own self-hosted original DeepSeek-V3: self-hosting keeps your data yours under an irrevocable grant (data-control strong, reliability strong), but the DeepSeek License Agreement imposes RAIL-style field-of-use restrictions that flow down to derivatives, holding use-and-modify to moderate - so ownership is partial, one step below the MIT V3 generations (deepseek-v3-mit), which reach substantial. For new work prefer the MIT generations unless you specifically need this checkpoint; where you do use it, honour the use restrictions, deploy behind your own guardrails, and treat EU high-stakes use as needing a self-assembled compliance package (with no open-source exemption on the licence axis).
Do you really own it?
Partial
none·limited·partial·substantial·full
Analytical input: AOI C · 64.4/100
The four ownership factors
Floor-weighted, not averaged. Nothing is weak, but use & modify is only moderate, so it misses the bar for substantial - strong on both use & modify and data control - and lands at partial.
1
Use and modify freelyCan you run, modify and adapt it with no gate and no field-of-use trap?
ModerateThe weight grant is irrevocable, royalty-free and permits commercial use and modification, but it is a non-OSI custom licence with binding RAIL-style field-of-use restrictions (no military, no unlawful use, no harm to minors, no automated legal-rights decisions, etc.) that flow down to derivatives - so use-and-modify is moderate, not strong. This is the material difference from the MIT V3 generations.
How this scores (AOI sub-dimensions)
Openness3/5how much is released - weights, data, code, licence - and how freelyOpen-weights tier: the weights are openly downloadable (ungated) with an open technical report, but the licence is conditional (use-restricted), the training data closed, the training code partial, evaluation partial.
Legal2/5how permissive and clean the licence is for real commercial useThe weight grant is irrevocable and permits commercial use, but it is a non-OSI custom licence with RAIL-style field-of-use restrictions on top of the family EU gap: no Article 55 documentation, no copyright policy, no training-content summary, and at 671B the open-source exemption does not apply (the licence is not FOSS).
2
TransparencyDo you know what it is: weights, training, behaviour, and legible terms?
ModerateWeights are inspectable and there is a detailed technical report, but the training data and code are closed, and the weights carry China-aligned topic filtering you cannot inspect - open_weights, so moderate.
How this scores (AOI sub-dimensions)
Provenance3/5how well we can trace and verify what went into the modelVerified deepseek-ai org on Hugging Face, safetensors distribution with checksums and a clear canonical source with no malicious-checkpoint incident (checklist ~5/8).
Governance3/5how accountable and well-documented the publisher isActive, named publisher (DeepSeek) with a verified org and a track record of technical reports, meeting the score-3 anchor.
3
ReliabilityIs it reliable and good enough for the job?
StrongPerformance 4, operational 5 and safety 3: a strong model with first-class serving; all three at or above 3 with two at or above 4, so reliability is strong. The caveat is the absence of a first-party guard model (and the un-tuned Base variant).
How this scores (AOI sub-dimensions)
Operational5/5how practical it is to run, serve and maintain in productionFirst-class ecosystem support: broad serving across vLLM, SGLang, llama.cpp and Ollama, an extensive family of community quantizations, and wide third-party hosting.
Safety3/5whether misuse risks are evaluated and guardrails are providedThe Chat variant is safety-tuned with documented behaviour, meeting the score-3 anchor, but safety tuning is lighter than Western frontier labs, the model exhibits China-aligned topic censorship, and no first-party guard model ships - deployers must add their own guardrails.
4
Doesn't extract your dataDoes running it keep your knowledge and data yours?
StrongSelf-hosted, the weights run entirely on your own infrastructure with no telemetry and an irrevocable grant, so your data stays yours and access cannot be clawed back. (The hosted DeepSeek API is a separate matter with its own data terms.)
How this scores
Not a scored AOI dimension. For a self-hosted model, data-control is a structural property of running the weights yourself, strong by default unless the model phones home or the licence claws back rights. For a hosted API this factor is the retention + train-on-inputs + residency read, scored from the binding terms.
How the AOI score is computed
The seven dimensions above, each scored 0 to 5, weighted and summed to the 0 to 100 headline. The score is the analytical input behind the ownership verdict, not the verdict itself.
DimensionScoreWeightPoints
Openness3/50.1810.8
Provenance3/50.169.6
Legal2/50.166.4
Safety3/50.169.6
Performance4/50.1411.2
Operational5/50.1212.0
Governance3/50.084.8
HeadlineC · 64.4/100
Sources
Every rating traces to a primary document. Read means the text was verified; unverified means it is known to exist but has not yet been read.
DocumentWhat it grounds
Licenceread2026-08-03
DeepSeek-V3 LICENSE-CODE / LICENSE-MODEL, read: "This code repository is licensed under the MIT License.
Model cardread2026-08-03
DeepSeek-V3 model card on the verified deepseek-ai HF org: 671B total / 37B active MoE, 128K context, safetensors, Base + Chat variants; first-class serving (vLLM, SGLang, llama.cpp, Ollama) and an extensive community quant ecosystem.
Third-party analysisunverified2026-08-03
On independent public leaderboards the original DeepSeek-V3 was competitive among large open-weight models at release (coding, maths, analysis); not OneHill-reproduced this session.
Third-party analysisunverified2026-08-03
Independent analysis notes DeepSeek open-weight models apply China-aligned content filtering on politically sensitive topics, with lighter safety tuning than Western frontier labs and no companion guard model.
Third-party analysisunverified2026-08-03
The DeepSeek License Agreement imposes field-of-use restrictions (non-FOSS), and no public EU AI Act training-content summary, copyright policy, or GPAI documentation package is published for DeepSeek-V3; the training corpus is not released.