DeepSeek V4.1 Flash 1017 vs @cf/meta/llama-3.2-1b-instruct

Compare DeepSeek V4.1 Flash 1017 and @cf/meta/llama-3.2-1b-instruct in this project through TrustedRouter.

1. Read https://trustedrouter.com/docs/llms.txt
2. Point the OpenAI-compatible client at
   https://api.trustedrouter.com/v1 and read the key from
   TRUSTEDROUTER_API_KEY.
3. Run our eval prompts on deepseek/deepseek-v4.1-flash-1017, then on meta-llama/llama-3.2-1b-instruct.
4. Show me cost, latency and quality side by side before changing the default.

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.trustedrouter.com/v1",
    api_key=os.environ["TRUSTEDROUTER_API_KEY"],
)
for model in ("deepseek/deepseek-v4.1-flash-1017", "meta-llama/llama-3.2-1b-instruct"):
    response = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": "What is the capital of France?"}],
    )
    print(model, response.choices[0].message.content)

for model in deepseek/deepseek-v4.1-flash-1017 meta-llama/llama-3.2-1b-instruct; do
  curl https://api.trustedrouter.com/v1/chat/completions \
    -H "Authorization: Bearer $TRUSTEDROUTER_API_KEY" \
    -H "Content-Type: application/json" \
    -d "{\"model\": \"$model\", \"messages\": [{\"role\": \"user\", \"content\": \"What is the capital of France?\"}]}"
done