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 | FLUX 3 Image Klein black-forest-labs/flux-3-image-klein | |
|---|---|---|
| Provider | Typesafe | Black Forest Labs |
| Family | FLUX | |
| Modality | text | image |
| Context window | 32,000 tok | — |
| Max output | 32,000 tok | — |
| Released | 2026-10-16 | 2026-10-16 |
| Input price | $0.042 /1M | $0.0090 /img |
| Output price | $0.0000 /1M | — |
| Cache read | — | — |
| Tools | — | — |
| Streaming | yes | — |
| Vision | — | — |
| 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.
FLUX 3 Image Klein is Black Forest Labs' 5.6B-parameter image model for text-to-image, image editing, and multi-reference generation with up to 10 reference images. It supports native 4K output and bounding-box layout control.
# 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 FLUX 3 Image Klein — same client, same key
client.chat.completions.create(
model="black-forest-labs/flux-3-image-klein",
messages=[{"role":"user","content":"hello"}],
)