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 | Whisper-Tiny-EN openai/whisper-tiny-en | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Family | Claude 4 | Whisper |
| Modality | text | audio-stt |
| Context window | 1,000,000 tok | — |
| Max output | 128,000 tok | — |
| Released | 2026-04-16 | 2024-04-22 |
| Input price | $5.00 /1M | $0.0005 /min |
| Output price | $25.00 /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.
Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. Trained on 680k hours of labelled data, Whisper models demonstrate a strong ability to generalize to many datasets and domains without the need for fine-tuning. This is the English-only version of the Whisper Tiny model which was trained on the task of speech recognition.
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 Whisper-Tiny-EN — same client, same key
client.chat.completions.create(
model="openai/whisper-tiny-en",
messages=[{"role":"user","content":"hello"}],
)