API Changelog

LM Studio 0.4.1

Anthropic-compatible API

• New Anthropic-compatible endpoint: POST /v1/messages.
  • Use Claude code models with LM Studio
  • See docs for more details: /docs/developer/anthropic-compat.

LM Studio 0.4.0

LM Studio native v1 REST API

• Official release of LM Studio's native v1 REST API at /api/v1/* endpoints.
  • MCP via API
  • Stateful chats
  • Authentication configuration with API tokens
  • Model download, load and unload endpoints
  • See overview page for more details and comparison with OpenAI-compatible endpoints.

LM Studio 0.3.29 • 2025‑10‑06

OpenAI /v1/responses and variant listing

• New OpenAI‑compatible endpoint: POST /v1/responses.
  • Stateful interactions via previous_response_id.
  • Custom tool calling and Remote MCP support (opt‑in).
  • Reasoning support with reasoning.effort for openai/gpt‑oss‑20b.
  • Streaming via SSE when stream: true.
• CLI: lms ls --variants lists all variants for multi‑variant models.
• Docs: /docs/developer/openai-compat. Full release notes: /blog/lmstudio-v0.3.29.

LM Studio 0.3.27 • 2025‑09‑24

CLI: model resource estimates, status, and interrupts

• New: lms load --estimate-only <model> prints estimated GPU and total memory before loading. Honors --context-length and --gpu, and uses an improved estimator that now accounts for flash attention and vision models.
• lms chat: press Ctrl+C to interrupt an ongoing prediction.
• lms ps --json now reports each model's generation status and the number of queued prediction requests.
• CLI color contrast improved for light mode.
• See docs: /docs/cli/local-models/load. Full release notes: /blog/lmstudio-v0.3.27.

LM Studio 0.3.26 • 2025‑09‑15

CLI log streaming: server + model

• lms log stream now supports multiple sources and filters.
  • --source server streams HTTP server logs (startup, endpoints, status)
  • --source model --filter input,output streams formatted user input and model output
  • Append --json for machine‑readable logs; --stats adds tokens/sec and related metrics (model source)
• See usage and examples: /docs/cli/serve/log-stream. Full release notes: /blog/lmstudio-v0.3.26.

LM Studio 0.3.25 • 2025‑09‑04

New model support (API)

• Added support for NVIDIA Nemotron‑Nano‑v2 with tool‑calling via the OpenAI‑compatible endpoints ‡.
• Added support for Google EmbeddingGemma for the /v1/embeddings endpoint ‡.

LM Studio 0.3.24 • 2025‑08‑28

Seed‑OSS tool‑calling and template fixes

• Added support for ByteDance/Seed‑OSS including tool‑calling and prompt‑template compatibility fixes in the OpenAI‑compatible API ‡.
• Fixed cases where tool calls were not parsed for certain prompt templates ‡.

LM Studio 0.3.23 • 2025‑08‑12

Reasoning content and tool‑calling reliability

• For gpt‑oss on POST /v1/chat/completions, reasoning content moves out of message.content and into choices.message.reasoning (non‑streaming) and choices.delta.reasoning (streaming), aligning with o3‑mini ‡.
• Tool names are normalized (e.g., snake_case) before being provided to the model to improve tool‑calling reliability ‡.
• Fixed errors for certain tools‑containing requests to POST /v1/chat/completions (e.g., "reading 'properties'") and non‑streaming tool‑call failures ‡.

LM Studio 0.3.19 • 2025‑07‑21

Bug fixes for streaming and tool calls

• Corrected usage statistics returned by OpenAI‑compatible streaming responses ‡.
• Improved handling of parallel tool calls via the streaming API ‡.
• Fixed parsing of correct tool calls for certain Mistral models ‡.

LM Studio 0.3.18 • 2025‑07‑10

Streaming options and tool‑calling improvements

• Added support for the stream_options object on OpenAI‑compatible endpoints. Setting stream_options.include_usage to true returns prompt and completion token usage during streaming ‡.
• Errors returned from streaming endpoints now follow the correct format expected by OpenAI clients ‡.
• Tool‑calling support added for Mistral v13 tokenizer models, using proper chat templates ‡.
• The response_format.type field now accepts "text" in chat‑completion requests ‡.
• Fixed bugs where parallel tool calls split across multiple chunks were dropped and where root‑level $defs in tool definitions were stripped ‡.

LM Studio 0.3.17 • 2025‑06‑25

Tool‑calling reliability and token‑count updates

• Token counts now include the system prompt and tool definitions ‡. This makes usage reporting more accurate for both the UI and the API.
• Tool‑call argument tokens are streamed as they are generated ‡, improving responsiveness when using streamed function calls.
• Various fixes improve MCP and tool‑calling reliability, including correct handling of tools that omit a parameters object and preventing hangs when an MCP server reloads ‡.

LM Studio 0.3.16 • 2025‑05‑23

Model capabilities in GET /models

• The OpenAI‑compatible REST API (/api/v0) now returns a capabilities array in the GET /models response. Each model lists its supported capabilities (e.g. "tool_use") ‡ so clients can programmatically discover tool‑enabled models.
• Fixed a streaming bug where an empty function name string was appended after the first packet of streamed tool calls ‡.

👾 LM Studio 0.3.15 • 2025-04-24

Release post: LM Studio 0.3.15

Improved Tool Use API Support

OpenAI-like REST API now supports the tool_choice parameter:

{
  "tool_choice": "auto" // or "none", "required"
}

• "tool_choice": "none" — Model will not call tools
• "tool_choice": "auto" — Model decides
• "tool_choice": "required" — Model must call tools (llama.cpp only)

Chunked responses now set "finish_reason": "tool_calls" when appropriate.

👾 LM Studio 0.3.14 • 2025-03-27

Release post: LM Studio 0.3.14

[API/SDK] Preset Support

RESTful API and SDKs support specifying presets in requests.

(example needed)

👾 LM Studio 0.3.10 • 2025-02-18

Release post: LM Studio 0.3.10

Speculative Decoding API

Enable speculative decoding in API requests with "draft_model":

{
  "model": "deepseek-r1-distill-qwen-7b",
  "draft_model": "deepseek-r1-distill-qwen-0.5b",
  "messages": [ ... ]
}

Responses now include a stats object for speculative decoding:

"stats": {
  "tokens_per_second": ...,
  "draft_model": "...",
  "total_draft_tokens_count": ...,
  "accepted_draft_tokens_count": ...,
  "rejected_draft_tokens_count": ...,
  "ignored_draft_tokens_count": ...
}

👾 LM Studio 0.3.9 • 2025-01-30

Release post: LM Studio 0.3.9

Idle TTL and Auto Evict

Set a TTL (in seconds) for models loaded via API requests (docs article: Idle TTL and Auto-Evict)

curl http://localhost:1234/api/v0/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-r1-distill-qwen-7b",
    "messages": [ ... ]
+   "ttl": 300,
}'

With lms:

lms load --ttl <seconds>

Separate reasoning_content in Chat Completion responses

For DeepSeek R1 models, get reasoning content in a separate field. See more here.

Turn this on in App Settings > Developer.

👾 LM Studio 0.3.6 • 2025-01-06

Release post: LM Studio 0.3.6

Tool and Function Calling API

Use any LLM that supports Tool Use and Function Calling through the OpenAI-like API.

Docs: Tool Use and Function Calling.

👾 LM Studio 0.3.5 • 2024-10-22

Release post: LM Studio 0.3.5

Introducing lms get: download models from the terminal

You can now download models directly from the terminal using a keyword

lms get deepseek-r1

or a full Hugging Face URL

lms get <hugging face url>

To filter for MLX models only, add --mlx to the command.

lms get deepseek-r1 --mlx