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-1-Schnell black-forest-labs/flux-1-schnell | Flux deepgram/flux | |
|---|---|---|
| Provider | Black Forest Labs | Deepgram |
| Family | FLUX | FLUX |
| Modality | image | audio-stt |
| Context window | — | — |
| Max output | — | — |
| Released | 2024-08-29 | 2025-09-29 |
| Input price | $0.0004 /img | $0.0077 /min |
| Output price | — | — |
| Cache read | — | — |
| Tools | — | — |
| Streaming | — | yes |
| Vision | — | — |
| JSON mode | — | — |
| Reasoning | — | — |
| Prompt caching | — | — |
FLUX.1 [schnell] is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions.
Flux is the first conversational speech recognition model built specifically for voice agents.
# 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-1-Schnell
client.chat.completions.create(
model="black-forest-labs/flux-1-schnell",
messages=[{"role":"user","content":"hello"}],
)
# Try Flux — same client, same key
client.chat.completions.create(
model="deepgram/flux",
messages=[{"role":"user","content":"hello"}],
)