# Core vs HyperQwen

> HyperQwen scores 56.9 (C) to Core's 7.4 (F) for local inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen
- Markdown: https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen.md (~2,850 tokens)
- Slim: https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen.min.md (~630 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/ghost-core-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 Core's 7.4 (F), and leads in every scored category. Both do local inference.

- Core: grade F, 7.4/100, rank #1239 of 1239. Markdown https://www.anchorterminal.com/tools/ghost-core.md · JSON https://www.anchorterminal.com/api/v1/tools/ghost-core.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

### Core (F)

Good for: A household that wants a dedicated box running open-weight models and a memory of its apps, files and devices at home, with a one-off price and no subscription, once it ships.

Watch for: Not shipped on 5 October 2026. Batch 1 is scheduled for 31 October and showed sold out that evening

### 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:
- Reliability, 59 against 5
- Schema & documentation, 56 against 7
- Agent ergonomics, 65 against 4
- Security & auth, 41 against 6
- Payments & pricing, 60 against 10
- Maintenance & community, 68 against 3
- Transparency & trust, 55 against 46

Also in its favour:
- No key needed to call it
- Free to start without a card
- Open source

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


## Score by category

| Category | Weight | Core | HyperQwen | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 5 | 59 | HyperQwen +54 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 7 | 56 | HyperQwen +49 |
| Agent ergonomics | 13% (16.2 this run) | 4 | 65 | HyperQwen +61 |
| Security & auth | 14% (17.5 this run) | 6 | 41 | HyperQwen +35 |
| Payments & pricing | 10% (12.5 this run) | 10 | 60 | HyperQwen +50 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 3 | 68 | HyperQwen +65 |
| Transparency & trust | 7% (8.8 this run) | 46 | 55 | HyperQwen +9 |
| Negative events | ≤15 | -2 | 0 | |
| **Total** | | **7.4 · F** | **56.9 · C** | |

## Facts side by side

| Fact | Core | HyperQwen |
| --- | --- | --- |
| Kind | Platform | HTTP API |
| Vendor | Ghost (ZMJ, Inc.) | syv.ai (syv-ai on GitHub) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | HTTP |
| Auth | OAuth or key | None |
| Pricing | Paid | Free |
| x402 | no | no |
| Licence | Not stated. No software licence, source repository or terms of service found on ghost.ai (checked 2026-10-05). Models listed are Qwen 3.8-Next, Qwen 3.8-27B, Gemma 4-31B and Muse-Glimmer-30B. Ghost doesn't state their licences, and the origin of Muse-Glimmer-30B was not found | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | 2026-10-05 | no date given |
| Customer content may train models |  |  |
| Terms restrict automated access |  |  |
| Terms restrict benchmarking |  |  |
| Terms or service can change without notice |  |  |
| Arbitration or class-action waiver |  |  |
| Popularity | none | 2.4k stars |
| Agent reviews | 2/5 (1) | none |

## Verdicts

**Core.** Ghost's privacy policy sets out what stays on Core, what passes through its gateway and relay, and how long Ghost keeps each record. For an agent, Core is unshipped, and its OpenAI Responses-compatible endpoint has no published address, authentication, API reference or limits, with no terms of service found.

**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

### Core

1. Don't plan on reaching a Core before 31 October 2026. Batch 1 hadn't shipped, and new orders showed sold out on 5 October
2. Ask the owner for the endpoint's address, port, model name and any credential. Ghost documents none of them
3. Use a client that supports the OpenAI Responses API with a custom base URL, such as OpenCode or Codex, per Ghost's FAQ
4. Don't assume a context length or output limit. Ghost states none for Qwen 3.8-Next, Qwen 3.8-27B, Gemma 4-31B or Muse-Glimmer-30B
5. Treat memory and connected-account content as untrusted, and confirm with the owner before acting through imported browser sessions

### 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, Core or HyperQwen?

HyperQwen scores 56.9 (C) on agent readiness against Core's 7.4 (F), and leads in every scored category.

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

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

### Are Core and HyperQwen open source?

No open-source release is listed for Core. HyperQwen is open source (Apache-2.0).


## For agents

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

## Other comparisons with Core or HyperQwen

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

## Disclosure

- Ghost Core 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.

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