compare/Claude Opus 5vsGemini 3.1 Pro

Claude Opus 5 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.
 Claude Opus 5
anthropic/claude-opus-5
Gemini 3.1 Pro
google/gemini-3.1-pro
ProviderAnthropicGoogle
FamilyClaude 4Gemini 3
Modalitytexttext
Context window1,000,000 tok1,000,000 tok
Max output128,000 tok65,536 tok
Released2026-07-242026-05-22
Input price$5.00 /1M$2.00 /1M
Output price$25.00 /1M$12.00 /1M
Cache read$0.200 /1M
Toolsyesyes
Streamingyesyes
Visionyesyes
JSON modeyesyes
Reasoningyesyes
Prompt cachingyes
Claude Opus 5
anthropic/claude-opus-5
Full spec →

Claude Opus 5 is Anthropic's model for complex agentic coding and enterprise work, delivering intelligence close to Claude Fable 5 at half the price. It uses adaptive thinking to calibrate reasoning per task and supports a one million token context window at standard pricing.

Strengths
  • General-purpose chat
  • Long context
  • Tool use
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 Claude Opus 5
client.chat.completions.create(
    model="anthropic/claude-opus-5",
    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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