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 Fable 5 anthropic/claude-fable-5 | Gemma-4-26b-A4b-IT google/gemma-4-26b-a4b-it | |
|---|---|---|
| Provider | Anthropic | |
| Family | Gemma | |
| Modality | text | text |
| Context window | 1,000,000 tok | 131,072 tok |
| Max output | 128,000 tok | 4,096 tok |
| Released | 2026-06-09 | 2026-04-02 |
| Input price | $10.00 /1M | $0.340 /1M |
| Output price | $50.00 /1M | $0.560 /1M |
| Cache read | — | — |
| Tools | yes | — |
| Streaming | yes | yes |
| Vision | yes | yes |
| JSON mode | yes | — |
| Reasoning | — | — |
| Prompt caching | — | — |
Claude Fable 5 is Anthropic's most capable widely released model, built for the most demanding reasoning and long-horizon agentic work. Adaptive thinking is always on, and the model supports a 1M token context window with up to 128k output tokens per request.
Gemma 4 is Google's most intelligent family of open models, built from Gemini 3 research to maximize intelligence-per-parameter.
# pip install aigateway-py openai
# aigateway-py: sub-accounts, evals, replays, jobs, webhook verify.
# openai SDK: chat/embeddings/images/audio — drop-in compat per our SDK's own guidance.
from openai import OpenAI
client = OpenAI(
base_url="https://api.aigateway.sh/v1",
api_key="sk-aig-...",
)
# Try Claude Fable 5
client.chat.completions.create(
model="anthropic/claude-fable-5",
messages=[{"role":"user","content":"hello"}],
)
# Try Gemma-4-26b-A4b-IT — same client, same key
client.chat.completions.create(
model="google/gemma-4-26b-a4b-it",
messages=[{"role":"user","content":"hello"}],
)