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.
| Flux-2-Klein-9b black-forest-labs/flux-2-klein-9b | Bria Text-to-Image HD bria/bria-text-to-image-hd | |
|---|---|---|
| Provider | Black Forest Labs | Bria |
| Family | FLUX | |
| Modality | image | image |
| Context window | — | — |
| Max output | — | — |
| Released | 2026-01-14 | — |
| Input price | $0.040 /img | $0.040 /img |
| Output price | — | — |
| Cache read | — | — |
| Tools | — | — |
| Streaming | — | — |
| Vision | — | — |
| JSON mode | — | — |
| Reasoning | — | — |
| Prompt caching | — | — |
FLUX.2 [klein] 9B is a 9 billion parameter model that can generate images from text descriptions and supports multi-reference editing capabilities.
Bria's Text-to-Image model for HD images. Trained exclusively on licensed data for safe and risk-free commercial use. Available also as source code and weights. For access to weights: https://bria.ai/contact-us
# 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 Flux-2-Klein-9b
client.chat.completions.create(
model="black-forest-labs/flux-2-klein-9b",
messages=[{"role":"user","content":"hello"}],
)
# Try Bria Text-to-Image HD — same client, same key
client.chat.completions.create(
model="bria/bria-text-to-image-hd",
messages=[{"role":"user","content":"hello"}],
)