compare/Embeddinggemma-300mvsGemma-3-12b-IT

Embeddinggemma-300m vs Gemma-3-12b-IT

Pricing, context window, capabilities, and release date — pulled from each provider's public docs. Both are available via the same AIgateway OpenAI-compatible endpoint; flip the model string to switch.

RUN BOTH LIVE

Paste a prompt. Watch them race.

Both models stream in parallel through your own AIgateway key. Tokens, latency, and cost update as they arrive.

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 Embeddinggemma-300m
google/embeddinggemma-300m
Gemma-3-12b-IT
google/gemma-3-12b-it
ProviderGoogleGoogle
FamilyGemmaGemma
Modalityembeddingtext
Context window—80,000 tok
Max output—4,096 tok
Released2025-09-042025-03-18
Input price$0.020 /1M$0.350 /1M
Output price—$0.560 /1M
Cache read——
Tools——
Streaming—yes
Visionyesyes
JSON mode——
Reasoning——
Prompt caching——
Embeddinggemma-300m
google/embeddinggemma-300m
Full spec →

EmbeddingGemma is a 300M parameter, state-of-the-art for its size, open embedding model from Google, built from Gemma 3 (with T5Gemma initialization) and the same research and technology used to create Gemini models. EmbeddingGemma produces vector representations of text, making it well-suited for search and retrieval tasks, including classification, clustering, and semantic similarity search. This model was trained with data in 100+ spoken languages.

Strengths
  • Semantic similarity
  • Vector search
Gemma-3-12b-IT
google/gemma-3-12b-it
Full spec →

Gemma 3 models are well-suited for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Gemma 3 models are multimodal, handling text and image input and generating text output, with a large, 128K context window, multilingual support in over 140 languages, and is available in more sizes than previous versions.

Strengths
  • General-purpose chat
  • Open-weight
SWITCH BETWEEN THEM

One key, both models, one line different.

# pip install aigateway-py openai
# aigateway-py: sub-accounts, evals, replays, jobs, webhook verify.
# openai SDK: chat/embeddings/images/audio — drop-in compat per our SDK's own guidance.
from openai import OpenAI

client = OpenAI(
    base_url="https://api.aigateway.sh/v1",
    api_key="sk-aig-...",
)

# Try Embeddinggemma-300m
client.chat.completions.create(
    model="google/embeddinggemma-300m",
    messages=[{"role":"user","content":"hello"}],
)

# Try Gemma-3-12b-IT — same client, same key
client.chat.completions.create(
    model="google/gemma-3-12b-it",
    messages=[{"role":"user","content":"hello"}],
)
Get an AIgateway keyAdd a third model

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