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.
Both models stream in parallel through your own AIgateway key. Tokens, latency, and cost update as they arrive.
| Claude Opus 4.7 anthropic/claude-opus-4.7 | Llama-3.1-8b-Instruct meta/llama-3.1-8b-instruct | |
|---|---|---|
| Provider | Anthropic | Meta |
| Family | Claude 4 | Llama 3 |
| Modality | text | text |
| Context window | 1,000,000 tok | 131,072 tok |
| Max output | 128,000 tok | 4,096 tok |
| Released | 2026-04-16 | 2024-07-23 |
| Input price | $5.00 /1M | $0.050 /1M |
| Output price | $25.00 /1M | $0.100 /1M |
| Cache read | $0.500 /1M | — |
| Tools | yes | — |
| Streaming | yes | yes |
| Vision | yes | — |
| JSON mode | yes | — |
| Reasoning | yes | — |
| Prompt caching | yes | — |
Claude Opus 4.7 is Anthropic's most capable generally available model to date. It is highly autonomous and performs exceptionally well on long-horizon agentic work, knowledge work, vision tasks, and memory tasks.
The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models. The Llama 3.1 instruction tuned text only models are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.
from openai import OpenAI
client = OpenAI(
base_url="https://api.aigateway.sh/v1",
api_key="sk-aig-...",
)
# Try Claude Opus 4.7
client.chat.completions.create(
model="anthropic/claude-opus-4.7",
messages=[{"role":"user","content":"hello"}],
)
# Try Llama-3.1-8b-Instruct — same client, same key
client.chat.completions.create(
model="meta/llama-3.1-8b-instruct",
messages=[{"role":"user","content":"hello"}],
)