Black Forest Labs
FLUX.2 Klein 4BTerbuka
Compact 4B FLUX.2 distilled for on-device and edge image generation.
Inteligensi
86.5 #38
AAQI 87.0
Kecepatan output
90 t/s
ITL 11.1 ms/tok
Harga gabungan (3:1)
$0.01 /1M
Input $0.01/M · Output $0.01/M
Konteks
32K
≈ 80 halaman A4 · output maks 4,096
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
FLUX.2 Klein 4B
Claude Mythos Preview (#1)
Average (68)
Sumbu radar diaproksimasi dari skor kategori jika pengukuran benchmark langsung tidak tersedia — lihat Metodologi.
Kelebihan & Trade-off
Di mana ia menang
- Runs fully on-device — no network, no fees
- ~6GB VRAM at Q4 — fits entry GPUs
- Fastest FLUX.2 tier at 90 img/s-class throughput
Hal yang perlu diperhatikan
- Noticeably below Pro on fine detail and text
- Low-resolution ceiling vs. 32B tiers
- Struggles with long, complex prompts
Kasus Penggunaan Killer
On-device apps
Offline image generation inside mobile/desktop apps.
Edge & IoT rendering
Local synthesis on embedded hardware.
Drafting loops
Cheap instant previews before a Pro render.
Quickstart Developer & API
Atur
HF_TOKEN dulu — dapatkan kunci APIcurl 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-4b",
"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-4b",
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-4b",
messages: [{ role: "user", content: "Refactor this function for O(n) time and explain the change." }],
}),
});
console.log((await res.json()).choices[0].message.content);Sumber Daya & Tautan Resmi
Deployment API
Bandingkan host & latensi
Throughput, TTFT, dan harga cache di Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock, dan Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Skor per sumber
Skor per kategori
Hasil benchmark
Spesifikasi Live & Arsitektur
Di balik kap
FLUX.2 Klein 4B — distilled on-device diffusion
- 4B distilled transformer — runs on phones and laptops
- Sub-second generation at 512–1024px
- Same prompt interface as Pro/Dev tiers
- Weights optimized for 6GB memory footprints
Tanggal rilis
14 Okt 2026
Arsitektur
FLUX.2 Klein 4B — distilled on-device diffusion
Parameter
4B
Lisensi
Open Weights
Jendela konteks
32,000 tokens
Output maks
4,096 tokens
Modalitas
text + image
Harga cache
baca $0.004 · tulis $0.0125 /1M
Penalaran
—
Harga input
$0.01/M
Harga output
$0.01/M
Kecepatan output
90 t/s
Waktu ke token pertama
—
Data diperbarui
22 Okt 2026
Perangkat Keras & Inferensi Lokal
Data: Convly AI (CC BY 4.0) ↗VRAM (4-bit Q4)
3 GB
GPU Min.
Any 6GB GPU
Estimasi tagihan bulanan
Estimasi pengeluaran bulanan
$0.00
Menghitung penghematan vs GPT-4o…
Kutip & sematkan
Badge Markdown GitHub
Loading badge markdown...BibTeX
@misc{llmpodium2026flux2klein4b,
title = {Benchmark Analysis and Intelligence Evaluation of FLUX.2 Klein 4B},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/flux-2-klein-4b}
}Sematkan Lencana Skor
Tambahkan lencana Podium Score langsung ke README GitHub atau Hugging Face Anda — menautkan ke peringkat langsung.
Pratinjau
Markdown
Loading badge snippet...HTML
Loading badge snippet...Lainnya dari Black Forest Labs
Model Alternatif
Alternatif terdekat untuk FLUX.2 Klein 4B berdasarkan kemampuan, harga, dan skor benchmark.