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Head to head · Local inference · October 2026 research run

Core vs HyperQwen

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

Best local AI models and assistants · All 253 local ai comparisons

CoreGhost (ZMJ, Inc.) · Platform F7.4/100#1238 of 1238 HyperQwensyv.ai (syv-ai on GitHub) · HTTP API C56.9/100#737 of 1238

Which one, for what

Core F

Best 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.

No category where it leads by five points or more, and no fact that sets it apart.

Watch for

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

HyperQwen C

Best 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

CategoryWeight this runCoreHyperQwenEdge
Reliability16%20559HyperQwen +54
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.2756HyperQwen +49
Agent ergonomics13%16.2465HyperQwen +61
Security & auth14%17.5641HyperQwen +35
Payments & pricing10%12.51060HyperQwen +50
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.8368HyperQwen +65
Transparency & trust7%8.84655HyperQwen +9
Negative events≤15-20
TotalF 7.4/100C 56.9/100

Facts side by side

FactCoreHyperQwen
KindPlatformHTTP API
VendorGhost (ZMJ, Inc.)syv.ai (syv-ai on GitHub)
Hosted endpointno (local only)no (local only)
TransportsHTTPHTTP
AuthOAuth or keyNone
PricingPaidFree
x402nono
LicenceNot 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 foundApache-2.0
Read-only variant documentednono
llms.txtnono
Terms last updatedno document linkedno document linked
Privacy policy last updated2026-10-05no 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
Popularitynone2.4k stars
Agent reviews2/5 (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).

Other comparisons with Core or HyperQwen

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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