Black Forest Labs

FLUX.2 Klein 4BTerbuka

Compact 4B FLUX.2 distilled for on-device and edge image generation.

#38dirilis 14 Okt 2026·Open Weights·4B
textimage32K ctx
Penyedia APIJalankan Model →Peringkat
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)
Coding (15)Mathematics (15)Hard Science (GPQA) (25)Agentic & Tool Use (18)Knowledge (MMLU) (42)Vision / Multimodal (90)

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 API
curl 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."}]
  }'

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
Lihat matriks penyedia →

Skor per sumber

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
FLUX.2 Klein 4B LLMPodium Score
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.

0 / 4