google/gemma-3-12b-it
Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...
A dedicated public landing page for this synced catalog row.
Synced from the active catalog
Validated for gateway requests
Charged from your UAI balance
Same API key and billing flow
This page exists for direct linking, onboarding, and SEO. The same model row powers /v1/models, the public catalog, the app pricing screen, and request validation for /v1/chat/completions.
The same model route, but with one account, one balance, and one API shape.
Use Google: Gemma 3 12B for multi-step prompts, planning, and deeper analysis while keeping the same OpenAI-compatible UAI endpoint.
Google: Gemma 3 12B exposes 131K tokens, which makes it a good fit for large documents, transcripts, and retrieval-heavy chat flows.
The synced capabilities for this row indicate image or vision support, so you can route multimodal requests through the same UAI account and billing flow.
Current synced numbers for this exact model row.
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Use this model with your UAI key over the standard OpenAI-compatible route.
Create a key in API Keys, then send requests to https://uai.sh/v1/chat/completions.
curl https://uai.sh/v1/chat/completions \
-H "Authorization: Bearer uai-YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "google/gemma-3-12b-it",
"messages": [{"role": "user", "content": "Say hi in one short sentence."}],
"stream": false
}'
from openai import OpenAI
client = OpenAI(base_url="https://uai.sh/v1", api_key="uai-YOUR_API_KEY")
response = client.chat.completions.create(
model="google/gemma-3-12b-it",
messages=[{"role": "user", "content": "Say hi in one short sentence."}],
stream=False
)
print(response.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://uai.sh/v1",
apiKey: "uai-YOUR_API_KEY"
});
const response = await client.chat.completions.create({
model: "google/gemma-3-12b-it",
messages: [{ role: "user", content: "Say hi in one short sentence." }],
stream: false
});
console.log(response.choices[0].message.content);
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