compare/FLUX 3 Image KleinvsMiniMax M3

FLUX 3 Image Klein vs MiniMax M3

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.

RUN BOTH LIVE

Paste a prompt. Watch them race.

Both models stream in parallel through your own AIgateway key. Tokens, latency, and cost update as they arrive.

Sign in to runLive streaming uses your own key. It's free to sign up.
 FLUX 3 Image Klein
black-forest-labs/flux-3-image-klein
MiniMax M3
minimax/m3
ProviderBlack Forest LabsMiniMax
FamilyFLUXMiniMax M
Modalityimagetext
Context window—1,000,000 tok
Max output—4,096 tok
Released2026-10-162026-06-01
Input price$0.0090 /img$0.300 /1M
Output price—$1.20 /1M
Cache read——
Tools——
Streaming—yes
Vision——
JSON mode——
Reasoning——
Prompt caching——
FLUX 3 Image Klein
black-forest-labs/flux-3-image-klein
Full spec →

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.

Strengths
  • Text-to-image generation
  • Creative control
MiniMax M3
minimax/m3
Full spec →

MiniMax's M3 language model with frontier coding and agentic capabilities, a 1M token context window, and multilingual support.

Strengths
  • General-purpose chat
  • Long context
  • Tool use
SWITCH BETWEEN THEM

One key, both models, one line different.

# 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 3 Image Klein
client.chat.completions.create(
    model="black-forest-labs/flux-3-image-klein",
    messages=[{"role":"user","content":"hello"}],
)

# Try MiniMax M3 — same client, same key
client.chat.completions.create(
    model="minimax/m3",
    messages=[{"role":"user","content":"hello"}],
)
Get an AIgateway keyAdd a third model

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