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poolsideLaguna M.1

A 225B total parameter Mixture-of-Experts model with 23B activated parameters per token designed for agentic coding and long-horizon work.

Model details

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Example usage

Laguna M.1 is a 225B total parameter Mixture-of-Experts model with 23B activated parameters per token designed for agentic coding and long-horizon work. Laguna M.1 uses global attention across all layers with 64 Q-heads, 8 KV-heads and softplus attention output gating. Apache 2.0 licensed.

This model was pre-trained on 30 trillion tokens and delivers the strongest performance in Poolside’s agent harness, pool, after undergoing agent RL. Poolside’s RL stack is a custom-built system loosely coupling the major components of inference and rollout generation, orchestration of code execution sandboxes, trajectory scoring, buffering and filtering, and distributed training.

Learn more here: https://poolside.ai/blog/introducing-laguna-xs2-m1.

Technical report: https://poolside.ai/assets/laguna/laguna-m1-xs2-technical-report.pdf

Input
1# You can use this model with any of the OpenAI clients in any language!
2# Simply set the API Key to get started
3
4import os
5from openai import OpenAI
6
7model_url = "" # Copy in from API pane in Baseten model dashboard
8
9client = OpenAI(
10    api_key=os.environ['BASETEN_API_KEY'],
11    base_url=model_url,
12)
13
14response = client.chat.completions.create(
15    model="poolside/laguna-m.1",
16    messages=[
17        {
18            "role": "user",
19            "content": "What is the time complexity of quicksort?"
20        }
21    ],
22    extra_body={
23        "chat_template_kwargs": {"enable_thinking": False}
24    },
25    stream=False,
26)
27
28print(response.model_dump_json(indent=2))
JSON output
1{
2    "id": "chatcmpl-def456",
3    "object": "chat.completion",
4    "model": "poolside/laguna-m.1",
5    "choices": [
6        {
7            "index": 0,
8            "message": {
9                "role": "assistant",
10                "reasoning_content": null,
11                "content": "Quicksort has the following time complexities:\n\n- **Best case**: O(n log n) — pivot consistently splits the array into equal halves.\n- **Average case**: O(n log n) — expected with random pivot selection.\n- **Worst case**: O(n²) — occurs when the pivot is always the smallest or largest element (e.g. already-sorted input with naive pivot choice).\n\nSpace complexity is O(log n) on average for the call stack.",
12                "tool_calls": null
13            },
14            "finish_reason": "stop"
15        }
16    ],
17    "usage": {
18        "prompt_tokens": 15,
19        "completion_tokens": 95,
20        "total_tokens": 110
21    }
22}

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