compare/Kimi K2.6vsGemini 3.1 Pro

Kimi K2.6 vs Gemini 3.1 Pro

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.
 Kimi K2.6
moonshot/kimi-k2.6
Gemini 3.1 Pro
google/gemini-3.1-pro
ProviderMoonshotGoogle
FamilyKimiGemini 3
Modalitytexttext
Context window262,144 tok1,000,000 tok
Max output16,384 tok65,536 tok
Released2026-04-202026-04-13
Input price$0.950 /1M$2.00 /1M
Output price$4.00 /1M$12.00 /1M
Cache read$0.160 /1M$0.200 /1M
Toolsyesyes
Streamingyesyes
Visionyesyes
JSON modeyesyes
Reasoningyesyes
Prompt cachingyesyes
Kimi K2.6
moonshot/kimi-k2.6
Full spec →

Kimi K2.6 is a frontier-scale open-source 1T parameter model with a 262.1k context window, multi-turn tool calling, vision inputs, and structured outputs for agentic workloads.

Strengths
  • Frontier-scale 1T parameters, open-weight
  • ~10× cheaper than Opus
  • Multi-turn tool calling + vision
Gemini 3.1 Pro
google/gemini-3.1-pro
Full spec →

Google's most intelligent Gemini model with improved reasoning, a medium thinking level, and a 1M token context window.

Strengths
  • 2M-token context
  • Native video + audio input
  • Cheapest long-context reasoning
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 Kimi K2.6
client.chat.completions.create(
    model="moonshot/kimi-k2.6",
    messages=[{"role":"user","content":"hello"}],
)

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

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