Pricing per million tokens, context window, capabilities — pulled from each provider's public docs. All 2 are available via the same AIgateway OpenAI-compatible endpoint; flip the model string to switch.
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.
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.
Source: each provider's published benchmarks. Higher is better. Run an eval to compare on your own data.
from openai import OpenAI
client = OpenAI(
base_url="https://api.aigateway.sh/v1",
api_key="sk-aig-...",
)
# Kimi-K2.6
client.chat.completions.create(
model="moonshot/kimi-k2.6",
messages=[{"role":"user","content":"hello"}],
)
# Llama-4-Scout-17b-16e-Instruct
client.chat.completions.create(
model="meta/llama-4-scout-17b-16e-instruct",
messages=[{"role":"user","content":"hello"}],
)