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.
| Pareto unbiased/pareto | FLUX 3 Image Klein black-forest-labs/flux-3-image-klein | |
|---|---|---|
| Provider | Unbiased | Black Forest Labs |
| Family | FLUX | |
| Modality | text | image |
| Context window | 262,144 tok | — |
| Max output | 32,768 tok | — |
| Released | 2026-09-17 | 2026-10-16 |
| Input price | $2.50 /1M | $0.0090 /img |
| Output price | $7.50 /1M | — |
| Cache read | — | — |
| Tools | — | — |
| Streaming | yes | — |
| Vision | — | — |
| JSON mode | — | — |
| Reasoning | — | — |
| Prompt caching | — | — |
Pareto is Unbiased's blended AI model. It engages multiple language models in parallel for each request, synthesizes one answer, and supports text and vision inputs through a single API response.
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 Pareto
client.chat.completions.create(
model="unbiased/pareto",
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"}],
)