compare/Gemma-3-12b-ITvsGemma-7b-IT-Lora

Gemma-3-12b-IT vs Gemma-7b-IT-Lora

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.

Sign in to runLive streaming uses your own key. It's free to sign up.
 Gemma-3-12b-IT
google/gemma-3-12b-it
Gemma-7b-IT-Lora
google/gemma-7b-it-lora
ProviderGoogleGoogle
FamilyGemmaGemma
Modalitytexttext
Context window80,000 tok3,500 tok
Max output4,096 tok4,096 tok
Released2025-03-182024-04-02
Input price$0.350 /1M$0.080 /1M
Output price$0.560 /1M$0.160 /1M
Cache read——
Tools——
Streamingyesyes
Visionyes—
JSON mode——
Reasoning——
Prompt caching——
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
Gemma-7b-IT-Lora
google/gemma-7b-it-lora
Full spec →

This is a Gemma-7B base model that Cloudflare dedicates for inference with LoRA adapters. Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models.

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 Gemma-3-12b-IT
client.chat.completions.create(
    model="google/gemma-3-12b-it",
    messages=[{"role":"user","content":"hello"}],
)

# Try Gemma-7b-IT-Lora — same client, same key
client.chat.completions.create(
    model="google/gemma-7b-it-lora",
    messages=[{"role":"user","content":"hello"}],
)
Get an AIgateway keyAdd a third model

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