# Docker Model Runner vs HyperQwen

> Docker Model Runner and HyperQwen score within a point of each other for local inference, 57.2 and 56.9 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

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- Updated: 2026-10-30

Docker Model Runner and HyperQwen score within a point of each other on agent readiness, 57.2 (C) and 56.9 (C). HyperQwen leads on schema & documentation, agent ergonomics and maintenance & community. Both do local inference.

- Docker Model Runner: grade C, 57.2/100, rank #728 of 1239. Markdown https://www.anchorterminal.com/tools/docker-model-runner.md · JSON https://www.anchorterminal.com/api/v1/tools/docker-model-runner.json
- HyperQwen: grade C, 56.9/100, rank #738 of 1239. Markdown https://www.anchorterminal.com/tools/hyperqwen.md · JSON https://www.anchorterminal.com/api/v1/tools/hyperqwen.json
- Best local AI models and assistants: https://www.anchorterminal.com/best/local-ai/index.md
- All 253 local ai comparisons: https://www.anchorterminal.com/compare/local-ai/index.md

## 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 59
- Transparency & trust, 74 against 55

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

### HyperQwen (C)

Good for: An operator with one 24 GB NVIDIA card who wants Qwen3.8-27B behind an OpenAI-compatible endpoint for a coding or tool-calling agent, with long context.

Ahead on:
- Schema & documentation, 56 against 49
- Agent ergonomics, 65 against 58
- Maintenance & community, 68 against 55

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

Watch for: Serves Qwen3.8-27B and checkpoints derived from it only. Other models are on the roadmap


## Score by category

| Category | Weight | Docker Model Runner | HyperQwen | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 85 | 59 | Docker Model Runner +26 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 49 | 56 | HyperQwen +7 |
| Agent ergonomics | 13% (16.2 this run) | 58 | 65 | HyperQwen +7 |
| Security & auth | 14% (17.5 this run) | 40 | 41 | HyperQwen +1 |
| 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 | 68 | HyperQwen +13 |
| Transparency & trust | 7% (8.8 this run) | 74 | 55 | Docker Model Runner +19 |
| Negative events | ≤15 | -3 | 0 | |
| **Total** | | **57.2 · C** | **56.9 · C** | |

## Facts side by side

| Fact | Docker Model Runner | HyperQwen |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Docker, Inc. | syv.ai (syv-ai on GitHub) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | 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 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-08-12 | none |
| Terms last updated | 2026-08-26 | no document linked |
| Privacy policy last updated | 2026-08-26 | no date given |
| Customer content may train models | not found in the text |  |
| Terms restrict automated access | yes |  |
| Terms restrict benchmarking | yes |  |
| Terms or service can change without notice | not found in the text |  |
| Arbitration or class-action waiver | yes |  |
| Popularity | 656 stars | 2.4k stars |

## 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.

**HyperQwen.** HyperQwen packages a patched vLLM 0.32.0 and requantised Qwen3.8-27B weights into one container with tool calling preset and a loopback bind when no key is set. It runs one model family, its speed figures come from one RTX 3090, and it has no versioned releases, changelog or security policy.

## 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

### HyperQwen

1. Call http://127.0.0.1:18020/v1 with model `qwen3.8-27b` and the `VLLM_API_KEY` value, or any string if no key was set
2. Poll `/health` before the first request. A first start downloads and prepares the model and compiles kernels, which can take over 30 minutes
3. Declare the context window your setup uses (65,536 by default, 131,072 for `CTX=long`, 245,760 for `CTX=huge`) so the client doesn't truncate
4. Ask the owner to set `VLLM_API_KEY` before setting `BIND=0.0.0.0`, and to front the port with a proxy that allowlists routes
5. Treat the README's tokens-per-second figures as the project's measurements on one RTX 3090 at 250 W

## Questions

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

Docker Model Runner and HyperQwen score within a point of each other on agent readiness, 57.2 (C) and 56.9 (C). HyperQwen leads on schema & documentation, agent ergonomics and maintenance & community.

### Do Docker Model Runner and HyperQwen need an API key?

Neither needs a key.

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

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

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

Yes. 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). HyperQwen is open source (Apache-2.0).


## For agents

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

## Other comparisons with Docker Model Runner or HyperQwen

- [AnythingLLM vs Docker Model Runner](https://www.anchorterminal.com/compare/anythingllm-vs-docker-model-runner.md)
- [AnythingLLM vs HyperQwen](https://www.anchorterminal.com/compare/anythingllm-vs-hyperqwen.md)
- [Berth vs Docker Model Runner](https://www.anchorterminal.com/compare/berth-vs-docker-model-runner.md)
- [Berth vs HyperQwen](https://www.anchorterminal.com/compare/berth-vs-hyperqwen.md)
- [BitRun vs Docker Model Runner](https://www.anchorterminal.com/compare/bitrun-vs-docker-model-runner.md)
- [BitRun vs HyperQwen](https://www.anchorterminal.com/compare/bitrun-vs-hyperqwen.md)
- [Docker Model Runner vs Foundry Local](https://www.anchorterminal.com/compare/docker-model-runner-vs-foundry-local.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 KoboldCpp](https://www.anchorterminal.com/compare/docker-model-runner-vs-koboldcpp.md)
- [Docker Model Runner vs Lemonade](https://www.anchorterminal.com/compare/docker-model-runner-vs-lemonade.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 MLX LM](https://www.anchorterminal.com/compare/docker-model-runner-vs-mlx-lm.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)
- [Docker Model Runner vs TextGen](https://www.anchorterminal.com/compare/docker-model-runner-vs-text-generation-webui.md)
- [Docker Model Runner vs vLLM](https://www.anchorterminal.com/compare/docker-model-runner-vs-vllm.md)
- [Foundry Local vs HyperQwen](https://www.anchorterminal.com/compare/foundry-local-vs-hyperqwen.md)
- [Core vs HyperQwen](https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen.md)
- [GPT4All vs HyperQwen](https://www.anchorterminal.com/compare/gpt4all-vs-hyperqwen.md)
- [HyperQwen vs Jan](https://www.anchorterminal.com/compare/hyperqwen-vs-jan.md)
- [HyperQwen vs Khoj](https://www.anchorterminal.com/compare/hyperqwen-vs-khoj.md)
- [HyperQwen vs KoboldCpp](https://www.anchorterminal.com/compare/hyperqwen-vs-koboldcpp.md)
- [HyperQwen vs Lemonade](https://www.anchorterminal.com/compare/hyperqwen-vs-lemonade.md)
- [HyperQwen vs llama.cpp](https://www.anchorterminal.com/compare/hyperqwen-vs-llama-cpp.md)
- [HyperQwen vs LM Studio](https://www.anchorterminal.com/compare/hyperqwen-vs-lm-studio.md)
- [HyperQwen vs LocalAI](https://www.anchorterminal.com/compare/hyperqwen-vs-localai.md)
- [HyperQwen vs MLX LM](https://www.anchorterminal.com/compare/hyperqwen-vs-mlx-lm.md)
- [HyperQwen vs Ollama](https://www.anchorterminal.com/compare/hyperqwen-vs-ollama.md)
- [HyperQwen vs Open WebUI](https://www.anchorterminal.com/compare/hyperqwen-vs-open-webui.md)
- [HyperQwen vs screenpipe](https://www.anchorterminal.com/compare/hyperqwen-vs-screenpipe.md)
- [HyperQwen vs TextGen](https://www.anchorterminal.com/compare/hyperqwen-vs-text-generation-webui.md)
- [HyperQwen vs vLLM](https://www.anchorterminal.com/compare/hyperqwen-vs-vllm.md)
- [Docker Model Runner vs Underdog](https://www.anchorterminal.com/compare/docker-model-runner-vs-underdog.md)
- [HyperQwen vs Underdog](https://www.anchorterminal.com/compare/hyperqwen-vs-underdog.md)

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