compare/Gemini 3.1 Flash LitevsGemini 3.1 Flash TTS

Gemini 3.1 Flash Lite vs Gemini 3.1 Flash TTS

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 3.1 Flash Lite
google/gemini-3.1-flash-lite
Gemini 3.1 Flash TTS
google/gemini-3.1-flash-tts
ProviderGoogleGoogle
FamilyGemini 3Gemini 3
Modalitytextaudio-tts
Context window1,000,000 tok
Max output8,192 tok
Released2026-05-222026-05-22
Input price$0.250 /1M$0.0000 /1K ch
Output price$1.50 /1M
Cache read$0.025 /1M
Toolsyesyes
Streamingyes
Visionyes
JSON modeyesyes
Reasoning
Prompt cachingyes
Gemini 3.1 Flash Lite
google/gemini-3.1-flash-lite
Full spec →

Google's lightest and most cost-efficient Gemini model for high-throughput tasks.

Strengths
  • Cheapest Gemini
  • Multi-modal native
  • Very fast
Gemini 3.1 Flash TTS
google/gemini-3.1-flash-tts
Full spec →

Newest audio model from Google introduces granular audio tags that give you precise control to direct AI speech for expressive audio generation.

Strengths
  • Natural speech synthesis
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 3.1 Flash Lite
client.chat.completions.create(
    model="google/gemini-3.1-flash-lite",
    messages=[{"role":"user","content":"hello"}],
)

# Try Gemini 3.1 Flash TTS — same client, same key
client.chat.completions.create(
    model="google/gemini-3.1-flash-tts",
    messages=[{"role":"user","content":"hello"}],
)
Get an AIgateway keyAdd a third model

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