Write a review

Head to head · Local inference · October 2026 research run

Berth vs Docker Model Runner

Berth scores 67.6 (B) on agent readiness against Docker Model Runner's 57.2 (C), and leads in 4 of 7 scored categories. Docker Model Runner leads on reliability and transparency & trust. Both do local inference.

Best local AI models and assistants · All 229 local ai comparisons

BerthTrevin Tindall (T-Crypt on GitHub) · HTTP API B67.6/100#283 of 1218 Docker Model RunnerDocker, Inc. · HTTP API C57.2/100#714 of 1218

Which one, for what

Berth B

Best for Someone running several GPU programs (llama.cpp, llama-swap, Ollama, vLLM, ComfyUI, games) on one NVIDIA card who wants them to take turns, and agents that need to ask for the card.

Ahead on

  • Schema & documentation, 69 against 49
  • Agent ergonomics, 75 against 58
  • Security & auth, 51 against 40
  • Maintenance & community, 76 against 55

Also in its favour

  • No incidents deducted, where Docker Model Runner loses 3 points for them

Watch for

First released on 11 October 2026 and called alpha. Windows, AMD and multiple GPUs are experimental, and the gateway is a preview

Docker Model Runner C

Best 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 76
  • Transparency & trust, 74 against 68

Also in its favour

  • No key needed to call it

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 runBerthDocker Model RunnerEdge
Reliability16%207685Docker Model Runner +9
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.26949Berth +20
Agent ergonomics13%16.27558Berth +17
Security & auth14%17.55140Berth +11
Payments & pricing10%12.56060even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87655Berth +21
Transparency & trust7%8.86874Docker Model Runner +6
Negative events≤150-3
TotalB 67.6/100C 57.2/100

Facts side by side

FactBerthDocker Model Runner
KindHTTP APIHTTP API
VendorTrevin Tindall (T-Crypt on GitHub)Docker, Inc.
Hosted endpointno (local only)no (local only)
TransportsHTTPHTTP
AuthAPI keyNone
PricingFreeFree
x402nono
LicenceApache-2.0. The Berth name, the Pilot mascot and the artwork in assets/ are excluded from the licence, per the NOTICE fileApache-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 release2026-10-232026-08-12
Terms last updatedno document linked2026-08-26
Privacy policy last updatedno document linked2026-08-26
Customer content may train modelsnot found in the text
Terms restrict automated accessyes
Terms restrict benchmarkingyes
Terms or service can change without noticenot found in the text
Arbitration or class-action waiveryes
Popularity245 stars656 stars

Verdicts

Berth

Berth coordinates one NVIDIA card between engines, ComfyUI and games, grants a lease only after the driver shows memory free, and gives agents a skill, JSON output and a keyed loopback gateway. It is 17 days old, alpha and maintained by one developer, with Windows and AMD experimental and no machine-readable API spec.

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

Berth

  1. Run berth status --format json before starting, stopping or switching any GPU engine. If berthd is unreachable, no engine is protected
  2. Never kill a process to free VRAM. Ask for the card with berth run, berth hold or a gateway request, and report stowaways to the user
  3. Send gateway requests to http://127.0.0.1:9799/v1 with Authorization: Bearer $(berth key), and use "stream": true for cold starts of up to minutes
  4. On a 503, read the code and wait for Retry-After. A pinned holder (a game or berth hold) answers 409 to stop and is the user's call
  5. Ask the user before berth reclaim LEASE --yes, any berth.toml edit or berth update. Each changes the node

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, Berth or Docker Model Runner?

Berth scores 67.6 (B) on agent readiness against Docker Model Runner's 57.2 (C), and leads in 4 of 7 scored categories. Docker Model Runner leads on reliability and transparency & trust.

Do Berth and Docker Model Runner need an API key?

Berth needs an API key. Docker Model Runner needs no key.

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

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

Are Berth and Docker Model Runner open source?

Yes. Berth is open source (Apache-2.0. The Berth name, the Pilot mascot and the artwork in assets/ are excluded from the licence, per the NOTICE file). 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 Berth or Docker Model Runner

Machine-readable

For companies

Do agents find, use and choose your tools?

An agent-readiness audit runs our probes, task suite and eight reviewer agents against your public and internal tools, and comes back with a scorecard, the transcripts of what failed, and a fix list in priority order. From $2,500, re-run included. We never take payment to move a rank. We do help companies earn one.

Get an auditSee a sample report