Model card

Gemini 3 Pro

lx1-gemini-3-proFrontierLive in the catalog

Built for scale: a million-token window and multimodal reasoning that stays coherent across enormous inputs. When a task means holding a whole codebase, a long document set, or a mix of text and images in view at once, this is the model that doesn't lose the thread.

Context window1M tokens

Input · per Mtok$2

Output · per Mtok$12

Served byLayer X1 engine

Where it earns its keep[01/03]

011M-token context for very large inputs
02Strong multimodal reasoning over text and images
03Holds coherence across long, mixed contexts

Capabilities

Tool callingYes

Strict, schema-faithful tool calls, enforced by the engine on every request — safe to build an agent loop on.

ReasoningYes

Thinks before it answers. Budget max_tokens generously — hidden reasoning counts against it.

VisionYes

Reads images — screenshots, diagrams, and UI states — inline in the conversation.

Behind the endpoint[02/03]

One endpoint. Served by our engine.

Gemini 3 Pro is served through the Layer X1 engine — zero-downtime serving is the design target, not a status-page apology. You request it by name; everything else is our problem.

Call it by name

curl https://api.layerx1.in/v1/messages \
  -H "x-api-key: lx1_your_key" \
  -H "content-type: application/json" \
  -d '{
    "model": "lx1-gemini-3-pro",
    "max_tokens": 1024,
    "messages": [{ "role": "user", "content": "Hello" }]
  }'

OpenAI-style clients work too — send the same model name to /v1/chat/completions with a Bearer key. See the docs for both dialects.

Your agent doesn't change.
Everything underneath does.

$export ANTHROPIC_BASE_URL=https://api.layerx1.in

Get a key Read the docs

Start free · no card · Starter from $5/mo

One endpoint. Served by our engine.

Your agent doesn't change.Everything underneath does.

Your agent doesn't change.
Everything underneath does.