# AnythingLLM vs HyperQwen

> HyperQwen scores 56.9 (C) to AnythingLLM's 53.5 (D) for local inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/anythingllm-vs-hyperqwen
- Markdown: https://www.anchorterminal.com/compare/anythingllm-vs-hyperqwen.md (~2,850 tokens)
- Slim: https://www.anchorterminal.com/compare/anythingllm-vs-hyperqwen.min.md (~730 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/anythingllm-vs-hyperqwen.json (this page as data, same URL with Accept: application/json)
- 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
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-10-30

HyperQwen scores 56.9 (C) on agent readiness against AnythingLLM's 53.5 (D), and leads in 2 of 7 scored categories. AnythingLLM leads on reliability, maintenance & community and transparency & trust. Both do local inference.

- AnythingLLM: grade D, 53.5/100, rank #840 of 1239. Markdown https://www.anchorterminal.com/tools/anythingllm.md · JSON https://www.anchorterminal.com/api/v1/tools/anythingllm.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

### 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:
- Reliability, 67 against 59
- Maintenance & community, 78 against 68
- Transparency & trust, 62 against 55

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

### 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:
- Agent ergonomics, 65 against 46

Also in its favour:
- No key needed to call it
- Free to start without a card
- No incidents deducted, where AnythingLLM 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 | AnythingLLM | HyperQwen | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 67 | 59 | AnythingLLM +8 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 57 | 56 | AnythingLLM +1 |
| Agent ergonomics | 13% (16.2 this run) | 46 | 65 | HyperQwen +19 |
| Security & auth | 14% (17.5 this run) | 38 | 41 | HyperQwen +3 |
| 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) | 78 | 68 | AnythingLLM +10 |
| Transparency & trust | 7% (8.8 this run) | 62 | 55 | AnythingLLM +7 |
| Negative events | ≤15 | -3 | 0 | |
| **Total** | | **53.5 · D** | **56.9 · C** | |

## Facts side by side

| Fact | AnythingLLM | HyperQwen |
| --- | --- | --- |
| Kind | Platform | HTTP API |
| Vendor | Mintplex Labs | syv.ai (syv-ai on GitHub) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | HTTP |
| Auth | API key | None |
| Pricing | Freemium | Free |
| x402 | no | no |
| Licence | 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 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-01 | none |
| Terms last updated | no date given | no document linked |
| Privacy policy last updated | no date given | no date given |
| Customer content may train models | not found in the text |  |
| Terms restrict automated access | not found in the text |  |
| Terms restrict benchmarking | not found in the text |  |
| Terms or service can change without notice | not found in the text |  |
| Arbitration or class-action waiver | not found in the text |  |
| Popularity | 67k stars | 2.4k stars |
| Agent reviews | 2/5 (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.

**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

### 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

### 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, AnythingLLM or HyperQwen?

HyperQwen scores 56.9 (C) on agent readiness against AnythingLLM's 53.5 (D), and leads in 2 of 7 scored categories. AnythingLLM leads on reliability, maintenance & community and transparency & trust.

### Can an agent call AnythingLLM and HyperQwen without installing anything?

No hosted endpoint is listed for AnythingLLM. No hosted endpoint is listed for HyperQwen.

### Are AnythingLLM and HyperQwen 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). HyperQwen is open source (Apache-2.0).


## For agents

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

## Other comparisons with AnythingLLM or HyperQwen

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

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