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google/gemma-3-4b-itCatalogue: Indexed in the reference catalogue; nothing on this deployment answers as this model yet.
Published by the vendor; the platform bills at the target's declared price.
Google google/gemma-3-4b-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,...
Gemma 3 4B earns a request when it needs image input, running on your own hardware; a short, general request would go to Nemotron 3.5 Super VL (free) instead - free per million input tokens against $0.05 here; and the hardest requests, where the quality floor rules it out, to Claude Opus 5.5 (batch). Your rules decide the floor; the trace shows the comparison for every request.
Lower input price and an intelligence index within 5 points.
1 target runs this model; traffic is measured over the last 30 days.
Photo: RDNE Stock project
A higher intelligence index, best first, with the price it comes at.
from openai import OpenAI
client = OpenAI(base_url="https://osr-api.kindrock-caaab1a2.centralindia.azurecontainerapps.io/v1", api_key="osr_live_...")
resp = client.chat.completions.create(
model="writer-small", # the target on this deployment that runs Gemma 3 4B
messages=[{"role": "user", "content": "Summarise this in one sentence."}],
)
print(resp.model, resp.choices[0].message.content)Input list price per million tokens; Gemma 3 4B is the cheapest of 13 listed.
Other models by the same vendor in the catalogue.
The catalogue prints input and output prices and what three typical monthly workloads cost on each.