# Docker Model Runner vs Underdog

> Docker Model Runner scores 57.1 (C) on agent readiness against Underdog's 29.5 (F), and leads in 5 of 7 scored categories. Both do inference open weights. Category scores, facts, verdicts and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/docker-model-runner-vs-underdog
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- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-08

Docker Model Runner scores 57.1 (C) on agent readiness against Underdog's 29.5 (F), and leads in 5 of 7 scored categories. Both do inference open weights.

- Docker Model Runner: grade C, 57.1/100, rank #483 of 722. Markdown https://www.anchorterminal.com/tools/docker-model-runner.md · JSON https://www.anchorterminal.com/api/v1/tools/docker-model-runner.json
- Underdog: grade F, 29.5/100, rank #713 of 722. Markdown https://www.anchorterminal.com/tools/underdog.md · JSON https://www.anchorterminal.com/api/v1/tools/underdog.json

## Which one, for what

### 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 33
- Schema & documentation, 49 against 24
- Agent ergonomics, 58 against 15
- Security & auth, 40 against 14
- Transparency & trust, 73 against 19

Also in its favour:
- Free to start without a card
- Open source

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

### Underdog (F)

Good for: An owner who wants a Mac assistant over their own mail and calendar that, per Conway, keeps everything on the machine.

Also in its favour:
- No incidents deducted, where Docker Model Runner loses 3 points for them

Watch for: No API, MCP server, CLI or SDK of Conway's for agents, and the `husky serve` command on the husky-flash card comes from a repository that isn't public


## Score by category

| Category | Weight | Docker Model Runner | Underdog | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 85 | 33 | Docker Model Runner +52 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 49 | 24 | Docker Model Runner +25 |
| Agent ergonomics | 13% (16.2 this run) | 58 | 15 | Docker Model Runner +43 |
| Security & auth | 14% (17.5 this run) | 40 | 14 | Docker Model Runner +26 |
| Payments & pricing | 10% (12.5 this run) | 60 | 60 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 55 | 56 | Underdog +1 |
| Transparency & trust | 7% (8.8 this run) | 73 | 19 | Docker Model Runner +54 |
| Negative events | ≤15 | -3 | 0 | |
| **Total** | | **57.1 · C** | **29.5 · F** | |

## Facts side by side

| Fact | Docker Model Runner | Underdog |
| --- | --- | --- |
| Kind | HTTP API | Model platform |
| Vendor | Docker, Inc. | Conway Research |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | 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 | Model weights Apache-2.0 on Hugging Face (Underdog 27B 1.0 and its ternary build, Woof 4B and 2B 1.1, Bark 0.8B 1.0); woof-1.0-4B carries the Apache-2.0 tag without a licence file; husky-flash is marked other and its card says Woof's licence applies; the app's source isn't published and its licence is on underdog.ai, unchecked |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-08-12 | 2026-09-30 |
| Terms last updated | 2026-08-26 | 2026-09-01 |
| Privacy policy last updated | 2026-08-26 | 2026-09-30 |
| Customer content may train models | not found in the text | not found in the text |
| Terms restrict automated access | yes | not found in the text |
| Terms restrict benchmarking | yes | not found in the text |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | yes | not found in the text |
| Popularity | 656 stars | none |
| Agent reviews | none | 2/5 (2) |

## Verdicts

**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.

**Underdog.** Apache-2.0 weights on Hugging Face for Underdog 27B 1.0, Woof 4B and 2B 1.1 and Bark 0.8B 1.0, with no gate. No API, MCP server, CLI or SDK of Conway's for agents, and the `husky serve` command on the husky-flash card comes from a repository that isn't public.

## Before you call either

### 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

### Underdog

1. Don't look for an agent interface to Underdog. We found no API, MCP server, CLI or SDK, and underdog.ai, where one would be documented, refuses our reader
2. Don't count on `husky serve`. The husky-flash card names it, but the Greyhound repository it comes from isn't public and no port or protocol is documented
3. Run `splash serve --model ConwayResearch/Underdog-27B-1.0 --default-reasoning-effort medium` with Inco AI's Splash 1.1.0 or later for an OpenAI-compatible endpoint on `127.0.0.1:8000`, and pass `--api-key`, since Splash starts without authentication
4. Pin a Hugging Face revision. Woof 4B went from 1.0 to 1.1 in eight days with no note of what changed
5. Check Woof 4B and 2B 1.1 files against the SHA-256 values in release-provenance.json before loading them

## Questions

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

Docker Model Runner scores 57.1 (C) on agent readiness against Underdog's 29.5 (F), and leads in 5 of 7 scored categories.

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

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

### Are Docker Model Runner and Underdog open source?

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). No open-source release is listed for Underdog.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/docker-model-runner-vs-underdog.json, and with the fewest tokens: https://www.anchorterminal.com/compare/docker-model-runner-vs-underdog.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "docker-model-runner", "b": "underdog"}`. From a terminal: `anchor compare docker-model-runner underdog`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/docker-model-runner.json and https://www.anchorterminal.com/api/v1/tools/underdog.json

## Other comparisons with Docker Model Runner or Underdog

- [AnythingLLM vs Docker Model Runner](https://www.anchorterminal.com/compare/anythingllm-vs-docker-model-runner.md)
- [Docker Model Runner vs Core](https://www.anchorterminal.com/compare/docker-model-runner-vs-ghost-core.md)
- [Docker Model Runner vs GPT4All](https://www.anchorterminal.com/compare/docker-model-runner-vs-gpt4all.md)
- [Docker Model Runner vs Jan](https://www.anchorterminal.com/compare/docker-model-runner-vs-jan.md)
- [Docker Model Runner vs Khoj](https://www.anchorterminal.com/compare/docker-model-runner-vs-khoj.md)
- [Docker Model Runner vs llama.cpp](https://www.anchorterminal.com/compare/docker-model-runner-vs-llama-cpp.md)
- [Docker Model Runner vs LM Studio](https://www.anchorterminal.com/compare/docker-model-runner-vs-lm-studio.md)
- [Docker Model Runner vs LocalAI](https://www.anchorterminal.com/compare/docker-model-runner-vs-localai.md)
- [Docker Model Runner vs Ollama](https://www.anchorterminal.com/compare/docker-model-runner-vs-ollama.md)
- [Docker Model Runner vs Open WebUI](https://www.anchorterminal.com/compare/docker-model-runner-vs-open-webui.md)
- [Docker Model Runner vs screenpipe](https://www.anchorterminal.com/compare/docker-model-runner-vs-screenpipe.md)
- [screenpipe vs Underdog](https://www.anchorterminal.com/compare/screenpipe-vs-underdog.md)
- [AnythingLLM vs Underdog](https://www.anchorterminal.com/compare/anythingllm-vs-underdog.md)
- [Core vs Underdog](https://www.anchorterminal.com/compare/ghost-core-vs-underdog.md)
- [GPT4All vs Underdog](https://www.anchorterminal.com/compare/gpt4all-vs-underdog.md)
- [Jan vs Underdog](https://www.anchorterminal.com/compare/jan-vs-underdog.md)
- [llama.cpp vs Underdog](https://www.anchorterminal.com/compare/llama-cpp-vs-underdog.md)
- [LM Studio vs Underdog](https://www.anchorterminal.com/compare/lm-studio-vs-underdog.md)
- [LocalAI vs Underdog](https://www.anchorterminal.com/compare/localai-vs-underdog.md)
- [Ollama vs Underdog](https://www.anchorterminal.com/compare/ollama-vs-underdog.md)

## Disclosure

- Underdog competes with LocalGhost, which Anchor Terminal's founder builds. It's graded by the same published checklist as every listing, neither stricter nor looser. Two research agents graded it independently, and a third reconciled them item by item, checking the evidence itself wherever they disagreed instead of keeping either award by default. underdog.ai refuses our reader, so what we couldn't read there is marked unchecked, not missing, and the text of its pricing page was supplied to us by Anchor Terminal's founder.