Gemini 3.8 Flash vs GPT-6 Astra Vergleich

// Gemini 3.8 Flash – agentische Coding-Aufgabe über das google-genai SDK (Python)
from google import genai

# GEMINI_API_KEY wird standardmäßig aus der Umgebung gelesen
client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3.8-flash",
    input=(
        "You are an autonomous coding agent. Run the test suite, "
        "fix the first failing test, and report a one-line summary."
    ),
    generation_config={
        # erlaubt: low | medium | high (minimal wird abgelehnt)
        "thinking_level": "high"
    },
)

print(interaction.output_text)

# Streaming-Variante für langfristige Agentenschleifen
stream = client.interactions.create(
    model="gemini-3.8-flash",
    input="Refactor the auth module and validate with the linter.",
    stream=True,
)
for event in stream:
    print(event)

// GPT-6 Astra – Reasoning-Aufgabe mit hohem Aufwand über das OpenAI SDK (Python)
import os
from openai import OpenAI

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

response = client.responses.create(
    model="gpt-6-astra",
    input=(
        "You are an autonomous coding agent working on a large refactor. "
        "Plan the steps, execute them, verify the result independently, "
        "and only report done once verification passes."
    ),
    reasoning={"effort": "high"},  # erlaubt: low | medium | high | xhigh | max
    max_output_tokens=4096,
)

print(response.output_text)

# Codex-CLI-Äquivalent (config.toml): Modell explizit auswählen, da
# die CLI inzwischen Migrationshinweise für ältere Modelle anzeigt
# [profile.default]
# model = "gpt-6-astra"
# model_reasoning_effort = "high"