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models / Meta / Llama 4 Scout 17B 16E Instruct

Llama 4 Scout 17B 16E Instruct

textmeta/llama-4-scout-17b-16e-instructZDR supported

Meta's Llama 4 Scout is a 17 billion parameter model with 16 experts that is natively multimodal. These models leverage a mixture-of-experts architecture to offer industry-leading performance in text and image understanding.

$0.85list priceper 1M output tokens
pricing
unitlist price
per 1M input tokens$0.27
per 1M output tokens$0.85

Everyone pays the list price. What comes back grows with your Reward Status: Noob 0.5% of every spend buys back $INFX, Pro (hold 1,337 $INFX) 2%, Elite (also hold 1,337 $XAVA) 5%. How it works

openai sdk (python)
from openai import OpenAI

client = OpenAI(
    base_url="https://xavainf.com/v1",
    api_key="xk_live_...",  # your Xava Inference key
)

r = client.chat.completions.create(
    model="meta/llama-4-scout-17b-16e-instruct",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(r.choices[0].message.content)
curl
curl https://xavainf.com/v1/chat/completions \
  -H "Authorization: Bearer $XINF_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"meta/llama-4-scout-17b-16e-instruct","messages":[{"role":"user","content":"Hello!"}]}'
limits
providerMeta
typetext
context window131,000 tokens
max output—
prompt storagenone
provider retentionnone ZDR supported
livesoon
requests 24h—
p50 latency—
uptime 7d—