Laguna M.1 APIOPEN WEIGHTS262K context

Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).

What is Laguna M.1?

Laguna M.1 is the flagship coding agent model from [Poolside](https://poolside.ai/), optimized for complex software engineering tasks. Designed for agentic coding workflows, it supports tool calling and reasoning, with a 256K...

Laguna M.1 pricing

Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):

On output price, Laguna M.1 is cheaper than 78% of the 309 models in the catalog.

What Laguna M.1 costs per month

Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.

Laguna M.1 vs alternatives

When not to use Laguna M.1

• It is served by a single provider, so there is less failover headroom during an outage.

Specs

How to call Laguna M.1

Copyfrom openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
    model="poolside/laguna-m.1",
    messages=[{"role": "user", "content": "Hello"}],
    # supports tools=[...] and tool_choice
)
print(resp.choices[0].message.content)

Copycurl https://api.datallmlab.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"poolside/laguna-m.1","messages":[{"role":"user","content":"Hello"}]}'

Copyimport OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
  model: "poolside/laguna-m.1",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);

The same key routes Laguna M.1 and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.

Prompting tips for Laguna M.1

• State the goal, not every step. Laguna M.1 reasons internally — give it the objective, constraints and success criteria and let it plan the approach; over-scripting each step tends to lower quality. Turn effort up for hard problems.
• Huge 262K context — but anchor the ask. You can paste whole documents or codebases; models attend most to the start and end, so put the key instruction at the top and restate it after long inputs.
• Give it real tools. Pass a tools=[...] schema instead of asking it to "pretend" — let Laguna M.1 emit tool calls, execute them, and feed results back for the next turn.
• Cheap enough to batch. Great for high-volume classification, extraction and drafting — template the prompt, batch requests, and validate outputs programmatically.

Tips are derived from Laguna M.1's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.

Open-source tools for Laguna M.1

Popular open-source projects for running and building with Laguna M.1 — star counts pulled from GitHub (July 2026).

Listed by GitHub stars; inclusion is by ecosystem relevance (inference engines, agent frameworks and SDKs), not affiliation. Stars change — see each repo for current numbers.

Migrating to Laguna M.1

Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → poolside/laguna-m.1. Messages, streaming, tool calls and the rest of your code stay the same. Routing & failover guide.

Self-host or use the API?

Laguna M.1 ships open weights (poolside/Laguna-M.1, ~3.4K downloads and 105 likes in the last 30 days), with community quantizations (fp4) for smaller GPUs, so you can run it yourself. Most teams still use the API: no GPU to provision or keep warm, no inference ops, and instant access across 1 providers with automatic failover. Self-host when data residency or fixed per-token economics matter most.

Rate limits & reliability

Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff. See the error-code guide and failover setup.

Related reading

Frequently asked questions