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vLLM, SGLang, Open WebUI vs AnythingLLM

Every row below is computed for the brief in section 01. Nothing here is a universal score.

Source
Registry and rules engines over one brief — nothing on this page is anchored in a fetched document yet
Evidence
none on this page — it links to the pages that hold it

01The brief this answers

No context was supplied, so this is a generic reading. Every figure below would move for a real brief.

The same tool can score differently for a different brief.

Objective
Local LLM
Also
Internal company search · Private company ChatGPT · Private LLM
Jurisdictions
none stated
Industry
unknown
Employees
unknown
Data
confidential yes · privileged unknown · personal likely · sensitive unknown
Local processing
not required
Cloud allowed
unknown
Users
unknown
Capability
unknown
Preference
no preference
Data risk
high

interpreted by: rules (deterministic mode) · confidence 40%

unresolved: organisation.industry, requirements.dataResidency, requirements.existingStack, budget, jurisdictions.primary, organisation.employees, data sensitivity, deploymentPreference, technicalCapability


Not accounted for

Nothing in this comparison depends on your industry, any residency requirement, the systems you already run, your budget, the jurisdiction you operate in, your headcount, how sensitive the material is, a hosting preference or the technical capability you have in-house — none of it was supplied. Where a figure would move for one of those, it is stated as an assumption rather than hidden inside the number.


02Comparison

4 subjects · 13 dimensions
DimensionvLLMToolSTRONG ALTERNATIVEfor self-hosted under this briefSGLangToolSTRONG ALTERNATIVEfor self-hosted under this briefOpen WebUIToolSTRONG ALTERNATIVEfor self-hosted under this briefAnythingLLMToolSTRONG ALTERNATIVEfor private cloud under this brief
Deployment modelRegistry entry: how this is delivered, and which solution class it is scored as.
Self-hosted

The registry records vLLM as available on self-hosted or private cloud or on-premise enterprise; it is scored here as self-hosted.

ASSESSMENT
Self-hosted

The registry records SGLang as available on self-hosted or private cloud or on-premise enterprise; it is scored here as self-hosted.

ASSESSMENT
Self-hosted

The registry records Open WebUI as available on self-hosted or private cloud or on-premise enterprise; it is scored here as self-hosted.

ASSESSMENT
Private cloud

The registry records AnythingLLM as available on self-hosted or private cloud; it is scored here as private cloud.

ASSESSMENT
Verdict for this briefSolution-class analysis (buildOptions) over this brief. The verdict is on the class of answer, not on the product.
STRONG ALTERNATIVE

For this brief — confidential documents — self-hosted is a strong alternative. Change the brief and this verdict changes.

RECOMMENDATION
STRONG ALTERNATIVE

For this brief — confidential documents — self-hosted is a strong alternative. Change the brief and this verdict changes.

RECOMMENDATION
STRONG ALTERNATIVE

For this brief — confidential documents — self-hosted is a strong alternative. Change the brief and this verdict changes.

RECOMMENDATION
STRONG ALTERNATIVE

For this brief — confidential documents — private cloud is a strong alternative. Change the brief and this verdict changes.

RECOMMENDATION
Functional fitOntology overlap between the objective in this brief and the use cases the registry records for the subject (matchRecipes).
100%

Covers your main objective (local LLM) and 3 of 3 secondary objectives (internal company search, private company ChatGPT, private LLM).

ASSESSMENT
73%

Covers your main objective (local LLM) and 1 of 3 secondary objectives (private LLM).

ASSESSMENT
100%

Covers your main objective (local LLM) and 3 of 3 secondary objectives (internal company search, private company ChatGPT, private LLM).

ASSESSMENT
87%

Covers your main objective (local LLM) and 2 of 3 secondary objectives (internal company search, private company ChatGPT).

ASSESSMENT
Deployment fitHosting preference, data egress, headcount band and technical capability, weighted 0.30 / 0.35 / 0.15 / 0.20 (matchRecipes).
74%

You stated no hosting preference, so no option is favoured on that basis. No hard restriction on where processing happens was stated. Headcount was not stated, so the size band could not be checked.

ASSESSMENT
74%

You stated no hosting preference, so no option is favoured on that basis. No hard restriction on where processing happens was stated. Headcount was not stated, so the size band could not be checked.

ASSESSMENT
74%

You stated no hosting preference, so no option is favoured on that basis. No hard restriction on where processing happens was stated. Headcount was not stated, so the size band could not be checked.

ASSESSMENT
74%

You stated no hosting preference, so no option is favoured on that basis. No hard restriction on where processing happens was stated. Headcount was not stated, so the size band could not be checked.

ASSESSMENT
Data controlExternal transfer computed from the architecture graph of the deployment (computeExternalTransfer) — what actually crosses out of your network.
none

External data transfer: none. Computed from “Local LLM inference server (Ollama / vLLM)”, the catalogue deployment that names vLLM and best matches this brief. No edge in this design crosses out of the company network.

ASSESSMENT
none

External data transfer: none. No catalogue deployment names SGLang, so this is read from “Private ChatGPT on your own server”, the best-matching self-hosted deployment for this brief. No edge in this design crosses out of the company network.

ASSESSMENT
none

External data transfer: none. Computed from “Private ChatGPT on your own server”, the catalogue deployment that names Open WebUI and best matches this brief. No edge in this design crosses out of the company network.

ASSESSMENT
some

External data transfer: some. No catalogue deployment names AnythingLLM, so this is read from “Private-cloud RAG in a single region”, the best-matching private cloud deployment for this brief. Confidential content leaves your premises for your own cloud tenancy ("VPN / private endpoint"). You keep control of the account; the provider is a processor, so a DPA and a documented region apply.

ASSESSMENT
Data residencyVendor documents we have fetched. A residency commitment we have not read is “unknown” — never assumed (CONTENT-RULES §5).
you decide

Self-hosted: the content stays wherever you run the server, so residency is a property of your own infrastructure rather than a vendor commitment.

ASSESSMENT
you decide

Self-hosted: the content stays wherever you run the server, so residency is a property of your own infrastructure rather than a vendor commitment.

ASSESSMENT
you decide

Self-hosted: the content stays wherever you run the server, so residency is a property of your own infrastructure rather than a vendor commitment.

ASSESSMENT
unknown

We hold no fetched residency commitment for AnythingLLM. That is a question to put to the vendor, not an assumption to make about them.

ASSESSMENT
Governance controlsThe four commitments a processor is asked for — DPA, subprocessor list, no training on your content, zero retention — counted against fetched vendor documents.
not applicable

Run on your own infrastructure, so the vendor questions apply only to whatever you still buy. We hold none of the four commitments for this subject, and for a self-hosted deployment none of them is required.

ASSESSMENT
not applicable

Run on your own infrastructure, so the vendor questions apply only to whatever you still buy. We hold none of the four commitments for this subject, and for a self-hosted deployment none of them is required.

ASSESSMENT
not applicable

Run on your own infrastructure, so the vendor questions apply only to whatever you still buy. We hold none of the four commitments for this subject, and for a self-hosted deployment none of them is required.

ASSESSMENT
unknown

We have fetched none of the four commitments for AnythingLLM: data processing agreement, subprocessor list, training on customer data, zero retention option. Each is a question for the vendor, and until it is answered it is unknown rather than absent.

ASSESSMENT
Integration effortThe FDE-day band the catalogue deployment was costed from (RECIPE_IMPLEMENTATION_DAYS).
2–6 FDE-days

2–6 FDE-days to implement. Computed from “Local LLM inference server (Ollama / vLLM)”, the catalogue deployment that names vLLM and best matches this brief.

ASSESSMENT
3–8 FDE-days

3–8 FDE-days to implement. No catalogue deployment names SGLang, so this is read from “Private ChatGPT on your own server”, the best-matching self-hosted deployment for this brief.

ASSESSMENT
3–8 FDE-days

3–8 FDE-days to implement. Computed from “Private ChatGPT on your own server”, the catalogue deployment that names Open WebUI and best matches this brief.

ASSESSMENT
6–15 FDE-days

6–15 FDE-days to implement. No catalogue deployment names AnythingLLM, so this is read from “Private-cloud RAG in a single region”, the best-matching private cloud deployment for this brief.

ASSESSMENT
Maintenance burdenWho operates the result, read from the solution class and the difficulty factors the deployment carries.
you operate it

You own GPU drivers and the model server, operating-system patching and backups. Assessed difficulty 2/5 is the shape of that work; someone has to hold it after go-live.

ASSESSMENT
you operate it

You own GPU drivers and the model server, operating-system patching and backups. Assessed difficulty 2/5 is the shape of that work; someone has to hold it after go-live.

ASSESSMENT
you operate it

You own GPU drivers and the model server, operating-system patching and backups. Assessed difficulty 2/5 is the shape of that work; someone has to hold it after go-live.

ASSESSMENT
you operate, provider hosts

You own GPU drivers and the model server, the identity integration and joiner/leaver process, operating-system patching and backups. Assessed difficulty 3/5 is the shape of that work; someone has to hold it after go-live.

ASSESSMENT
Deployment difficultyDifficulty 1–5 for the deployment and for this team (scoreDifficulty): the same stack scores lower for an organisation with its own engineers.
2/5

2/5. Starting point 2/5: software you install, run and keep running on your own machines. +0.5 You run the model server yourself: GPU drivers, quantisation choice, memory headroom and restarts are all yours to own.

ASSESSMENT
2/5

2/5. Starting point 2/5: software you install, run and keep running on your own machines. +0.5 You run the model server yourself: GPU drivers, quantisation choice, memory headroom and restarts are all yours to own.

ASSESSMENT
2/5

2/5. Starting point 2/5: software you install, run and keep running on your own machines. +0.5 You run the model server yourself: GPU drivers, quantisation choice, memory headroom and restarts are all yours to own.

ASSESSMENT
3/5

3/5. Starting point 2/5: your own tenancy to build in, but no hardware to buy or rack. +0.5 You run the model server yourself: GPU drivers, quantisation choice, memory headroom and restarts are all yours to own.

ASSESSMENT
Estimated costIndicative cost for this headcount (estimateCost), plus any per-token price we have actually fetched. A price we have not read is not printed.
USD 5,500 – 21,000

USD 5,500 – 21,000 — one-off — for vLLM at this headcount. Computed from “Local LLM inference server (Ollama / vLLM)”, the catalogue deployment that names vLLM and best matches this brief.

ASSESSMENT
USD 6,300 – 24,000

USD 6,300 – 24,000 — one-off — for SGLang at this headcount. No catalogue deployment names SGLang, so this is read from “Private ChatGPT on your own server”, the best-matching self-hosted deployment for this brief.

ASSESSMENT
USD 6,300 – 24,000

USD 6,300 – 24,000 — one-off — for Open WebUI at this headcount. Computed from “Private ChatGPT on your own server”, the catalogue deployment that names Open WebUI and best matches this brief.

ASSESSMENT
USD 5,200 – 30,000

USD 5,200 – 30,000 — one-off plus monthly, read as first-year outlay — for AnythingLLM at this headcount. No catalogue deployment names AnythingLLM, so this is read from “Private-cloud RAG in a single region”, the best-matching private cloud deployment for this brief.

ASSESSMENT
CustomisationRegistry entry: whether the source is open and where the deployment can be changed.
source available

The registry files vLLM as open source, so the interface, retrieval behaviour and the model behind it can be changed — subject to the licence, which is a fetched fact on its own page.

ASSESSMENT
source available

The registry files SGLang as open source, so the interface, retrieval behaviour and the model behind it can be changed — subject to the licence, which is a fetched fact on its own page.

ASSESSMENT
source available

The registry files Open WebUI as open source, so the interface, retrieval behaviour and the model behind it can be changed — subject to the licence, which is a fetched fact on its own page.

ASSESSMENT
source available

The registry files AnythingLLM as open source, so the interface, retrieval behaviour and the model behind it can be changed — subject to the licence, which is a fetched fact on its own page.

ASSESSMENT
Relevant compliance evidenceThe compliance engine over this brief and this subject (assessCompliance), with each issue cited to the instrument it quotes where the page was fetched.
7 issues · 0 cited

7 issues spotted for this brief, 0 of them legal requirements; 0 carry a quote from the instrument they rest on. Leading with: Self-hosting moves the security obligation to you.

ASSESSMENT
7 issues · 0 cited

7 issues spotted for this brief, 0 of them legal requirements; 0 carry a quote from the instrument they rest on. Leading with: Self-hosting moves the security obligation to you.

ASSESSMENT
7 issues · 0 cited

7 issues spotted for this brief, 0 of them legal requirements; 0 carry a quote from the instrument they rest on. Leading with: Self-hosting moves the security obligation to you.

ASSESSMENT
9 issues · 0 cited

9 issues spotted for this brief, 0 of them legal requirements; 0 carry a quote from the instrument they rest on. Leading with: Confidentiality duties bind independently of data protection law.

ASSESSMENT

Add one that serves the same objective

This table is full at 4 subjects. Remove one to add another — beyond four, the columns stop being readable and the comparison stops being one.

  • Continue
  • LiteLLM
  • llama.cpp
  • LM Studio
  • LocalAI
  • Ollama
  • Tabby

03What this does not tell you

  • WARNINGCompare no jurisdictioncompare_no_jurisdiction

    No jurisdiction was supplied, so only the cross-cutting rules ran. A comparison for a regulated deployment should name one.

  • MINORCompare objective derivedcompare_objective_derived

    No objective was given, so functional fit is measured against local LLM — the use case most of these subjects share. Add one to the link to measure a different job.

  • MINORCompare recipe substitutedcompare_recipe_substituted

    No catalogue deployment names SGLang, so its cost, effort and difficulty are read from “Private ChatGPT on your own server”, the closest self-hosted deployment for this brief.

  • MINORCompare recipe substitutedcompare_recipe_substituted

    No catalogue deployment names AnythingLLM, so its cost, effort and difficulty are read from “Private-cloud RAG in a single region”, the closest private cloud deployment for this brief.

Structured issue-spotting to support your own review — not legal advice. Verify against the cited primary sources and your counsel.


04Evidence

0 records

No sources were recorded for this answer. Nothing on this page should be treated as verified.


05Next