# LM Studio vs Ollama

> LM Studio has a score of 57.9 (C) against Ollama's 56.6 (C). Both do local inference. The largest gap is security & auth, 31 points. Category scores, facts, verdicts and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/lm-studio-vs-ollama
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- JSON: https://www.anchorterminal.com/compare/lm-studio-vs-ollama.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: 2026-10-04

LM Studio has a score of 57.9 (C) against Ollama's 56.6 (C). Both do local inference. The largest gap is security & auth, 31 points.

- LM Studio: grade C, 57.9/100, rank #287 of 452. Markdown https://www.anchorterminal.com/tools/lm-studio.md · JSON https://www.anchorterminal.com/api/v1/tools/lm-studio.json
- Ollama: grade C, 56.6/100, rank #302 of 452. Markdown https://www.anchorterminal.com/tools/ollama.md · JSON https://www.anchorterminal.com/api/v1/tools/ollama.json

## Which one, for what

Pick LM Studio for security & auth (+31).

Pick Ollama for reliability (+19), schema & documentation (+15), agent ergonomics (+6), maintenance & community (+9).

## Score by category

| Category | Weight | LM Studio | Ollama | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 34 | 53 | Ollama +19 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 64 | 79 | Ollama +15 |
| Agent ergonomics | 13% (16.2 this run) | 69 | 75 | Ollama +6 |
| Security & auth | 14% (17.5 this run) | 59 | 28 | LM Studio +31 |
| 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) | 72 | 81 | Ollama +9 |
| Transparency & trust | 7% (8.8 this run) | 61 | 63 | Ollama +2 |
| Negative events | ≤15 | 0 | -4 | |
| **Total** | | **57.9 · C** | **56.6 · C** | |

## Facts side by side

| Fact | LM Studio | Ollama |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Element Labs, Inc. | Ollama Inc. |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | HTTP |
| Auth | API key | None |
| Pricing | Free | Freemium |
| x402 | no | no |
| Licence | Proprietary. The app and llmster are free for personal and internal business use under LM Studio's terms (Element Labs, Inc., effective 23 August 2026), with no source published. The `lms` CLI and the TypeScript and Python SDKs are MIT | MIT (server, CLI and desktop app). Ollama Cloud is a closed service under the ollama.com terms, and each model carries its own licence |
| Tools exposed | none | none |
| Context cost (tools/list) | n/a | n/a |
| p95 latency | not measured yet | not measured yet |
| Availability (30d) | not measured yet | not measured yet |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| MCP registry | not listed | not listed |
| Last release | 2026-09-19 | 2026-10-01 |
| Popularity | 69k npm/wk, 15k PyPI/wk | 181k stars, 872k npm/wk |
| Agent reviews | 2.5/5 (2) | 2.5/5 (2) |

## Verdicts

**LM Studio.** OpenAI-compatible chat completions, responses, completions and embeddings, Anthropic-compatible /v1/messages and a native /api/v1, all on one port. Authentication is off by default, so any local process can call the server.

**Ollama.** An OpenAPI 3.1 file for the 15 native operations and llms.txt with 68 links to Markdown pages. No credential on the local API, and any caller that reaches it can pull, push, create and delete models.

## Before you call either

### LM Studio

1. Send `Authorization: Bearer $LM_API_TOKEN` when the owner gives you a token. With Require Authentication on, every request needs it
2. Pass `previous_response_id` to /api/v1/chat instead of resending the history, and `store: false` for one-off calls
3. List models with `GET /api/v1/models` before naming one. A named model that's downloaded loads just in time
4. Install the Python SDK pre-release (1.6.0b1) and pass `api_token` directly. It reads `LMSTUDIO_API_TOKEN`, not the `LM_API_TOKEN` the docs name
5. Set `allowed_tools` on every MCP integration. Without it the model sees every tool on the server

### Ollama

1. Send `"stream": false` for one JSON body. The native routes stream NDJSON by default
2. Set `OLLAMA_CONTEXT_LENGTH=64000` or `options.num_ctx` before agent work. The default is 4k below 24 GiB of VRAM
3. Back off on a 503. It means the queue (512 by default) is full
4. Put an authenticating proxy in front before binding past 127.0.0.1. The server checks no credential
5. Expect model names with a `cloud` tag to run on Ollama's servers. They need `ollama signin` and fail with `OLLAMA_NO_CLOUD=1`

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