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Head to head · Local inference · October 2026 research run

Core vs MLX LM

MLX LM scores 52.2 (D) on agent readiness against Core's 7.3 (F), and leads in every scored category. Both do local inference.

CoreGhost (ZMJ, Inc.) · Model platform F7.3/100#841 of 841 MLX LMApple Inc. · HTTP API D52.2/100#657 of 841

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.

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

MLX LM D

Good for An owner with an Apple silicon Mac who wants MLX-format models, local fine-tuning and quantisation from Python or the command line, with a simple local chat completions server.

Ahead on

  • Reliability, 66 against 5
  • Schema & documentation, 37 against 7
  • Agent ergonomics, 54 against 4
  • Security & auth, 32 against 6
  • Payments & pricing, 60 against 10
  • Maintenance & community, 61 against 3
  • Transparency & trust, 66 against 45

Also in its favour

  • No key needed to call it
  • Free to start without a card
  • Open source

Watch for

mlx_lm.server has no API key or other credential option, and --allowed-origins defaults to *

Score by category

CategoryWeight this runCoreMLX LMEdge
Reliability16%20566MLX LM +61
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.2737MLX LM +30
Agent ergonomics13%16.2454MLX LM +50
Security & auth14%17.5632MLX LM +26
Payments & pricing10%12.51060MLX LM +50
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.8361MLX LM +58
Transparency & trust7%8.84566MLX LM +21
Negative events≤15-20
Total7.3 · F52.2 · D

Facts side by side

FactCoreMLX LM
KindModel platformHTTP API
VendorGhost (ZMJ, Inc.)Apple Inc.
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 foundMIT
Read-only variant documentednono
llms.txtnono
Last releasenone2026-10-01
Terms last updatedno document linkedno document linked
Privacy policy last updated2026-10-05no document linked
Customer content may train models
Terms restrict automated access
Terms restrict benchmarking
Terms or service can change without notice
Arbitration or class-action waiver
Popularitynone7.3k stars, 140k PyPI/wk
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.

MLX LM

MIT, with no telemetry found in the source, and the tests passed on the last eight pushes to main. mlx_lm.server has no API key option, answers any origin by default and loads whichever model a request names, and its own docs say it is not recommended for production.

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

MLX LM

  1. Keep mlx_lm.server on 127.0.0.1 and pass --allowed-origins with the origins you trust. There is no API key, and the default answers every origin
  2. Treat any caller as able to load any model. The model and adapters request fields accept any Hugging Face repository or local path
  3. Send max_tokens or max_completion_tokens when you need more than 512 tokens, the server default
  4. Read errors as {"error": "<text>"} with 400 for a bad field and 404 for a model that failed to load. They are not OpenAI error objects
  5. Poll GET /health before the first request. It answers 503 with unavailable when the generation thread has stopped

Questions

Which is better for AI agents, Core or MLX LM?

MLX LM scores 52.2 (D) on agent readiness against Core's 7.3 (F), and leads in every scored category.

Can an agent call Core and MLX LM without installing anything?

No hosted endpoint is listed for Core. No hosted endpoint is listed for MLX LM.

Are Core and MLX LM open source?

No open-source release is listed for Core. MLX LM is open source (MIT).

Other comparisons with Core or MLX LM

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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