compare/Gemini 3.6 FlashvsMiniMax M3

Gemini 3.6 Flash vs MiniMax M3

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 3.6 Flash
google/gemini-3.6-flash
MiniMax M3
minimax/m3
ProviderGoogleMiniMax
FamilyGemini 3MiniMax M
Modalitytexttext
Context window1,048,576 tok1,000,000 tok
Max output65,536 tok4,096 tok
Released2026-07-212026-06-01
Input price$1.50 /1M$0.300 /1M
Output price$7.50 /1M$1.20 /1M
Cache read
Toolsyes
Streamingyesyes
Visionyes
JSON modeyes
Reasoning
Prompt caching
Gemini 3.6 Flash
google/gemini-3.6-flash
Full spec →

Gemini 3.6 Flash provides sustained frontier-level intelligence optimized for real-world tasks at a higher speed and lower cost, excelling at code generation, agentic execution, and spatial reasoning.

Strengths
  • General-purpose chat
  • Long context
  • Tool use
MiniMax M3
minimax/m3
Full spec →

MiniMax's M3 language model with frontier coding and agentic capabilities, a 1M token context window, and multilingual support.

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 3.6 Flash
client.chat.completions.create(
    model="google/gemini-3.6-flash",
    messages=[{"role":"user","content":"hello"}],
)

# Try MiniMax M3 — same client, same key
client.chat.completions.create(
    model="minimax/m3",
    messages=[{"role":"user","content":"hello"}],
)
Get an AIgateway keyAdd a third model

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