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.
| Jev 1.14 typesafe/jev-1.14.0 | Gemini 2.5 Pro google/gemini-2.5-pro | |
|---|---|---|
| Provider | Typesafe | |
| Family | ||
| Modality | text | text |
| Context window | 32,000 tok | 1,000,000 tok |
| Max output | 32,000 tok | 65,536 tok |
| Released | 2026-10-16 | 2026-05-22 |
| Input price | $0.042 /1M | $1.25 /1M |
| Output price | $0.0000 /1M | $10.00 /1M |
| Cache read | — | — |
| Tools | — | — |
| Streaming | yes | yes |
| Vision | — | yes |
| JSON mode | — | — |
| Reasoning | — | — |
| Prompt caching | — | — |
Jev 1.14 is TypeSafe's structured evaluation model. It evaluates one state against typed Noul, Choice, Score, and Box questions and returns calibrated answers with probabilities and confidence. Image inputs and Box questions are beta and dreamer-ready, not recommended for production.
Google's most capable Gemini 2.5 model with strong reasoning, thinking support, and a 1M token context window.
# 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 Jev 1.14
client.chat.completions.create(
model="typesafe/jev-1.14.0",
messages=[{"role":"user","content":"hello"}],
)
# Try Gemini 2.5 Pro — same client, same key
client.chat.completions.create(
model="google/gemini-2.5-pro",
messages=[{"role":"user","content":"hello"}],
)