# Lemonade vs MLX LM

> Lemonade scores 63.8 (B) on agent readiness against MLX LM's 52.2 (D), and leads in 5 of 7 scored categories. Both do local inference. Category scores, facts, verdicts and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/lemonade-vs-mlx-lm
- Markdown: https://www.anchorterminal.com/compare/lemonade-vs-mlx-lm.md (~2,550 tokens)
- Slim: https://www.anchorterminal.com/compare/lemonade-vs-mlx-lm.min.md (~530 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/lemonade-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

Lemonade scores 63.8 (B) on agent readiness against MLX LM's 52.2 (D), and leads in 5 of 7 scored categories. Both do local inference.

- Lemonade: grade B, 63.8/100, rank #336 of 842. Markdown https://www.anchorterminal.com/tools/lemonade.md · JSON https://www.anchorterminal.com/api/v1/tools/lemonade.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

### Lemonade (B)

Good for: An owner with AMD hardware (Ryzen AI NPUs, Radeon or Strix Halo) who wants one local server for chat, speech and images that existing OpenAI, Anthropic or Ollama clients can call, and for MCP clients that want local models as tools.

Ahead on:
- Reliability, 75 against 66
- Schema & documentation, 70 against 37
- Agent ergonomics, 70 against 54
- Maintenance & community, 76 against 61

Watch for: No authentication by default. With no key set, every route answers, including `/internal/*` shutdown and configuration

### 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.

Also in its favour:
- No key needed to call it

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


## Score by category

| Category | Weight | Lemonade | MLX LM | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 75 | 66 | Lemonade +9 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 70 | 37 | Lemonade +33 |
| Agent ergonomics | 13% (16.2 this run) | 70 | 54 | Lemonade +16 |
| Security & auth | 14% (17.5 this run) | 36 | 32 | Lemonade +4 |
| 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) | 76 | 61 | Lemonade +15 |
| Transparency & trust | 7% (8.8 this run) | 64 | 66 | MLX LM +2 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **63.8 · B** | **52.2 · D** | |

## Facts side by side

| Fact | Lemonade | MLX LM |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | AMD and the Lemonade community | Apple Inc. |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | HTTP |
| Auth | API key | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache 2.0. Each backend (llama.cpp, whisper.cpp, stable-diffusion.cpp, FastFlowLM and others) is downloaded separately under its own licence | MIT |
| Tools exposed | 6 | none |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-07 | 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 | 5.8k stars | 7.3k stars, 140k PyPI/wk |

## Verdicts

**Lemonade.** Apache 2.0, with weekly releases, installers for Windows, macOS and five Linux routes, and a six-tool MCP endpoint whose descriptions steer a caller away from accidental multi-gigabyte downloads. Authentication is off by default, the repository has no security policy, and the docs tell WebSocket clients to pass the key in the URL.

**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

### Lemonade

1. Call `lemonade_list_models` (or `GET /v1/models`) before naming a model. A wrong name with `allow_download: true` can start a multi-gigabyte download
2. Send `Authorization: Bearer <key>` when the operator has set `LEMONADE_API_KEY`. `/internal/*` needs the admin key when one is set
3. Use `POST /v1/chat/completions` for streamed tokens, embeddings and speech. The MCP endpoint ignores `stream` and has no embeddings or text-to-speech tool
4. Pass `output_dir` to `lemonade_generate_image` and `lemonade_omni` to get file paths in place of inline base64. Writes stay inside the MCP media sandbox
5. Read `GET /v1/docs` on the running server for the reference that matches its version. Weekly releases change behaviour

### 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, Lemonade or MLX LM?

Lemonade scores 63.8 (B) on agent readiness against MLX LM's 52.2 (D), and leads in 5 of 7 scored categories.

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

Lemonade needs an API key. MLX LM needs no key.

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

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

### Are Lemonade and MLX LM open source?

Yes. Lemonade is open source (Apache 2.0. Each backend (llama.cpp, whisper.cpp, stable-diffusion.cpp, FastFlowLM and others) is downloaded separately under its own licence). MLX LM is open source (MIT).


## For agents

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

## Other comparisons with Lemonade or MLX LM

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