Black Forest Labs
FLUX.2 Klein 9BOpen
9B FLUX.2 klein tier — near-Pro quality on a single consumer GPU.
Intelligence
88.2 #28
AAQI 88.0
Output Speed
55 t/s
ITL 18.2 ms/tok
Blended price (3:1)
$0.02 /1M
In $0.02/M · Out $0.02/M
Context
64K
≈ 160 A4 pages · max out 4,096
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
FLUX.2 Klein 9B
Claude Mythos Preview (#1)
Average (68)
Radar axes are approximated from category scores where direct benchmark measurements are missing — see Methodology.
Strengths & Trade-offs
Where it wins
- Best quality-per-GB in the FLUX.2 family
- Runs on RTX 3060-class hardware
- Open weights — fine-tune and self-host freely
Trade-offs to watch
- Still trails Dev/Pro on typography and faces
- Half the speed of the 4B klein tier
- 2K output ceiling
Killer Use Cases
Hobbyist & indie pipelines
Pro-adjacent images on consumer cards.
Fine-tuned niche styles
Small enough to iterate LoRAs overnight.
Local production tools
Self-hosted rendering for studios and agencies.
Developer Quickstart & API
Set
HF_TOKEN first — get an API keycurl https://router.huggingface.co/v1/chat/completions \
-H "Authorization: Bearer $HF_TOKEN" \
-H "content-type: application/json" \
-d '{
"model": "black-forest-labs/FLUX.2-klein-9b",
"messages": [{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}]
}'import os
from openai import OpenAI
client = OpenAI(
base_url="https://router.huggingface.co/v1",
api_key=os.environ["HF_TOKEN"],
)
resp = client.chat.completions.create(
model="black-forest-labs/FLUX.2-klein-9b",
messages=[{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}],
)
print(resp.choices[0].message.content)const res = await fetch("https://router.huggingface.co/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.HF_TOKEN}`,
"content-type": "application/json",
},
body: JSON.stringify({
model: "black-forest-labs/FLUX.2-klein-9b",
messages: [{ role: "user", content: "Refactor this function for O(n) time and explain the change." }],
}),
});
console.log((await res.json()).choices[0].message.content);Official Resources & Links
API deployment
Compare hosts & latency
Throughput, TTFT and cache pricing across Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock and Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Scores by Source
Category Scores
Benchmark Results
Head-to-head Live Matchups
Live Specs & Architecture
Under the hood
FLUX.2 Klein 9B — consumer-GPU diffusion
- 9B distilled transformer — the klein quality tier
- Fits 8GB VRAM at Q4
- Near-Pro prompt adherence on standard scenes
- Full LoRA fine-tuning support
Release date
Oct 14, 2026
Architecture
FLUX.2 Klein 9B — consumer-GPU diffusion
Parameters
9B
License
Open Weights
Context Window
64,000 tokens
Max Output
4,096 tokens
Modalities
text + image
Cache Pricing
read $0.008 · write $0.025 /1M
Reasoning
—
Input Price
$0.02/M
Output Price
$0.02/M
Output Speed
55 t/s
Time to First Token
—
Data Updated
Oct 22, 2026
Hardware & Local Inference
Data: Convly AI (CC BY 4.0) ↗VRAM (4-bit Q4)
6 GB
Min GPU
RTX 3060 8GB / any 8GB GPU
Estimated monthly bill
Estimated monthly spend
$0.00
Calculating savings vs GPT-4o...
Cite & embed
GitHub Markdown badge
Loading badge markdown...BibTeX
@misc{llmpodium2026flux2klein9b,
title = {Benchmark Analysis and Intelligence Evaluation of FLUX.2 Klein 9B},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/flux-2-klein-9b}
}Embed Score Badge
Add a live Podium Score badge to your GitHub or Hugging Face README — it links back to the live ranking.
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