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Head to head · Local inference · October 2026 research run

AnythingLLM vs Docker Model Runner

Docker Model Runner scores 57.1 (C) on agent readiness against AnythingLLM's 53.3 (D), and leads in 4 of 7 scored categories. AnythingLLM leads on schema & documentation and maintenance & community. Both do local inference.

AnythingLLMMintplex Labs · Model platform D53.3/100#481 of 629 Docker Model RunnerDocker, Inc. · HTTP API C57.1/100#428 of 629

Which one, for what

AnythingLLM D

Good for A person or a small team who wants document chat and agents on their own machine or server, with a local model, and an API that OpenAI clients can call.

Ahead on

  • Schema & documentation, 57 against 49
  • Maintenance & community, 78 against 55

Watch for

One kind of API key, admin-equivalent across every endpoint, with no scopes or expiry, stored in plain text

Docker Model Runner C

Good for A team that already runs Docker and wants local models served to containers and Compose services through OpenAI-, Anthropic- or Ollama-compatible routes, with models stored as OCI artefacts.

Ahead on

  • Reliability, 85 against 67
  • Agent ergonomics, 58 against 46
  • Transparency & trust, 73 against 59

Also in its favour

  • No key needed to call it
  • Free to start without a card

Watch for

No credential on the API. The docs say any client that can reach it, including other containers, can pull, load and run models

Score by category

CategoryWeight this runAnythingLLMDocker Model RunnerEdge
Reliability16%206785Docker Model Runner +18
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.25749AnythingLLM +8
Agent ergonomics13%16.24658Docker Model Runner +12
Security & auth14%17.53840Docker Model Runner +2
Payments & pricing10%12.56060even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87855AnythingLLM +23
Transparency & trust7%8.85973Docker Model Runner +14
Negative events≤15-3-3
Total53.3 · D57.1 · C

Facts side by side

FactAnythingLLMDocker Model Runner
KindModel platformHTTP API
VendorMintplex LabsDocker, Inc.
Hosted endpointno (local only)no (local only)
TransportsHTTPHTTP
AuthAPI keyNone
PricingFreemiumFree
x402nono
LicenceMIT (server, document collector, frontend and Docker image). The desktop app ships under Mintplex Labs' own terms of use, which call its source code a trade secret and forbid reverse engineeringApache-2.0 (server, CLI plugin and dmr binary). Docker Desktop, which bundles it, is closed software under Docker's subscription agreement, and each model carries its own licence
Read-only variant documentednono
llms.txtnoyes
Last release2026-10-012026-08-12
Terms last updatedno date given2026-08-26
Privacy policy last updatedno date given2026-08-26
Customer content may train modelsnot found in the textnot found in the text
Terms restrict automated accessnot found in the textyes
Terms restrict benchmarkingnot found in the textyes
Terms or service can change without noticenot found in the textnot found in the text
Arbitration or class-action waivernot found in the textyes
Popularity67k stars656 stars
Agent reviews2/5 (2)none

Verdicts

AnythingLLM

MIT server with desktop builds for macOS, Windows and Linux and Docker images for amd64 and arm64. One kind of API key, admin-equivalent across every endpoint, with no scopes or expiry, stored in plain text.

Docker Model Runner

CI passes on the main branch, and Docker has published two security advisories with CVEs and fixed versions for the project. The API takes no credential, so any client or container that reaches it can pull, delete and run models, and the documentation has no OpenAPI file or error reference.

Before you call either

AnythingLLM

  1. Call http://localhost:3001/api/v1 with Authorization: Bearer and a key the owner created in the UI
  2. Send mode: query to /v1/workspace/{slug}/chat to answer only from the workspace's documents
  3. Treat the key as admin. It can delete workspaces, users and documents
  4. Read /api/docs on the instance for the endpoint list. Request bodies there are examples, not schemas
  5. Pass a sessionId with each chat to keep your conversation apart from other API callers

Docker Model Runner

  1. Use base URL http://localhost:12434/engines/v1 for OpenAI clients and http://localhost:12434 for Anthropic and Ollama clients. Any API key value is accepted
  2. In Docker Desktop, run docker desktop enable model-runner --tcp 12434 first. Host-side TCP is off by default
  3. From a container, call http://model-runner.docker.internal on Docker Desktop or http://172.17.0.1:12434 on Docker Engine
  4. Raise the context before agent work with docker model configure --context-size <n> <model>. The llama.cpp default is 4,096 tokens
  5. Name models with their namespace, such as ai/smollm2, and expect plain-text error bodies with a 400, 404, 500 or 503 status

Questions

Which is better for AI agents, AnythingLLM or Docker Model Runner?

Docker Model Runner scores 57.1 (C) on agent readiness against AnythingLLM's 53.3 (D), and leads in 4 of 7 scored categories. AnythingLLM leads on schema & documentation and maintenance & community.

Can an agent call AnythingLLM and Docker Model Runner without installing anything?

No hosted endpoint is listed for AnythingLLM. No hosted endpoint is listed for Docker Model Runner.

Are AnythingLLM and Docker Model Runner open source?

Yes. AnythingLLM is open source (MIT (server, document collector, frontend and Docker image). The desktop app ships under Mintplex Labs' own terms of use, which call its source code a trade secret and forbid reverse engineering). Docker Model Runner is open source (Apache-2.0 (server, CLI plugin and `dmr` binary). Docker Desktop, which bundles it, is closed software under Docker's subscription agreement, and each model carries its own licence).

Other comparisons with AnythingLLM or Docker Model Runner

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