compare/Gemini 3.7 FlashvsGemini 3.5 Flash-Lite

Gemini 3.7 Flash vs Gemini 3.5 Flash-Lite

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.
 Gemini 3.7 Flash
google/gemini-3.7-flash
Gemini 3.5 Flash-Lite
google/gemini-3.5-flash-lite
ProviderGoogleGoogle
FamilyGemini 3Gemini 3
Modalitytexttext
Context window1,048,576 tok1,048,576 tok
Max output65,536 tok65,536 tok
Released2026-08-142026-07-21
Input price$0.750 /1M$0.300 /1M
Output price$3.75 /1M$2.50 /1M
Cache read
Toolsyesyes
Streamingyesyes
Visionyesyes
JSON modeyesyes
Reasoning
Prompt caching
Gemini 3.7 Flash
google/gemini-3.7-flash
Full spec →

Gemini 3.7 Flash is a highly capable, natively multimodal reasoning model optimized for agentic workflows and real-world tasks.

Strengths
  • General-purpose chat
  • Long context
  • Tool use
Gemini 3.5 Flash-Lite
google/gemini-3.5-flash-lite
Full spec →

Gemini 3.5 Flash-Lite is a low-latency, cost-effective multimodal model optimized for high-throughput, low-cost execution for subagent tasks and document parsing.

Strengths
  • General-purpose chat
  • Long context
  • Tool use
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 Gemini 3.7 Flash
client.chat.completions.create(
    model="google/gemini-3.7-flash",
    messages=[{"role":"user","content":"hello"}],
)

# Try Gemini 3.5 Flash-Lite — same client, same key
client.chat.completions.create(
    model="google/gemini-3.5-flash-lite",
    messages=[{"role":"user","content":"hello"}],
)
Get an AIgateway keyAdd a third model

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