# KoboldCpp vs MLX LM

> KoboldCpp scores 60.5 (C) on agent readiness against MLX LM's 52.2 (D), and leads in 5 of 7 scored categories. MLX LM leads on transparency & trust. Both do local inference. Category scores, facts, verdicts and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/koboldcpp-vs-mlx-lm
- Markdown: https://www.anchorterminal.com/compare/koboldcpp-vs-mlx-lm.md (~2,450 tokens)
- Slim: https://www.anchorterminal.com/compare/koboldcpp-vs-mlx-lm.min.md (~530 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/koboldcpp-vs-mlx-lm.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
- Updated: 2026-10-09

KoboldCpp scores 60.5 (C) on agent readiness against MLX LM's 52.2 (D), and leads in 5 of 7 scored categories. MLX LM leads on transparency & trust. Both do local inference.

- KoboldCpp: grade C, 60.5/100, rank #462 of 842. Markdown https://www.anchorterminal.com/tools/koboldcpp.md · JSON https://www.anchorterminal.com/api/v1/tools/koboldcpp.json
- MLX LM: grade D, 52.2/100, rank #657 of 842. Markdown https://www.anchorterminal.com/tools/mlx-lm.md · JSON https://www.anchorterminal.com/api/v1/tools/mlx-lm.json

## Which one, for what

### KoboldCpp (C)

Good for: An owner who wants text, image, speech and music models behind one executable with a writing and roleplay interface, and clients that speak the KoboldAI, OpenAI, Ollama or Anthropic formats.

Ahead on:
- Schema & documentation, 68 against 37
- Agent ergonomics, 63 against 54
- Security & auth, 38 against 32
- Maintenance & community, 82 against 61

Watch for: With no `--host` the server accepts connections on all routable interfaces, and no password is set by default

### 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:
- Transparency & trust, 66 against 49

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


## Score by category

| Category | Weight | KoboldCpp | MLX LM | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 68 | 66 | KoboldCpp +2 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 68 | 37 | KoboldCpp +31 |
| Agent ergonomics | 13% (16.2 this run) | 63 | 54 | KoboldCpp +9 |
| Security & auth | 14% (17.5 this run) | 38 | 32 | KoboldCpp +6 |
| 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) | 82 | 61 | KoboldCpp +21 |
| Transparency & trust | 7% (8.8 this run) | 49 | 66 | MLX LM +17 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **60.5 · C** | **52.2 · D** | |

## Facts side by side

| Fact | KoboldCpp | MLX LM |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | LostRuins (Concedo) | Apple Inc. |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | HTTP |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | AGPL-3.0 for KoboldCpp and KoboldAI Lite. The bundled GGML, llama.cpp and stable-diffusion.cpp code stays under MIT | MIT |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-09-27 | 2026-10-01 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no 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 |  |  |
| Popularity | 12k stars | 7.3k stars, 140k PyPI/wk |

## Verdicts

**KoboldCpp.** One file runs text, image, speech and music models behind a published OpenAPI 3.0.3 document, with eight releases in 90 days. The server listens on every interface with no password by default, and `--password` leaves the image routes open.

**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

### KoboldCpp

1. Start with `--host 127.0.0.1` and `--password`. The default listens on every interface with no key
2. Send the password as `Authorization: Bearer <password>`. It is not read from the query string
3. Treat 503 as both busy and rate limited. The server never sends 429 or `Retry-After`, and the wait in seconds is in `detail.msg`
4. Pass `max_length` or `max_tokens`. The default is 2,048 tokens unless `--defaultgenamt` changes it
5. Send a `genkey` with each generation so `/api/extra/generate/check` and `/api/extra/abort` act on your request and not another caller's

### 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, KoboldCpp or MLX LM?

KoboldCpp scores 60.5 (C) on agent readiness against MLX LM's 52.2 (D), and leads in 5 of 7 scored categories. MLX LM leads on transparency & trust.

### Do KoboldCpp and MLX LM need an API key?

Neither needs a key.

### Can an agent call KoboldCpp and MLX LM without installing anything?

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

### Are KoboldCpp and MLX LM open source?

Yes. KoboldCpp is open source (AGPL-3.0 for KoboldCpp and KoboldAI Lite. The bundled GGML, llama.cpp and stable-diffusion.cpp code stays under MIT). MLX LM is open source (MIT).


## For agents

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

## Other comparisons with KoboldCpp or MLX LM

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