DeepSeek

DeepSeek V4 FlashTerbuka

Name: DeepSeek V4 Flash
Price: 0.28 USD
Rating: 42 (11 reviews)
Author: DeepSeek

DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows.

#403dirilis 30 Jul 2026·Open Weights·Not disclosed

text1.0M ctx

Penyedia API Dapatkan Kunci API →Peringkat

Inteligensi

42.0 #403

AAQI 50.0

Kecepatan output

113 t/s

TTFT 1.34 s · ITL 8.8 ms/tok

Harga gabungan (3:1)

$0.175 /1M

Input $0.14/M · Output $0.28/M

Konteks

1.0M

≈ 2,500 halaman A4 · output maks 16,384

Quality Domain Radar

6-Axis Frontier Evaluation vs Category Average & Flagship

DeepSeek V4 Flash

Claude Mythos Preview (#1)

Average (68)

Sumbu radar diaproksimasi dari skor kategori jika pengukuran benchmark langsung tidak tersedia — lihat Metodologi.

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

Arena.ai ↗

1438.0

#79 · 48.4k votes · ±4

Artificial Analysis ↗

Skor per kategori

Nilai100.0 Konteks panjang99.2 Matematika62.0 Intelligence51.8 Penalaran41.2 Coding38.0 Agen35.3 Kecepatan22.0 Pengetahuan12.5

Hasil benchmark

LiveCodeBench91.6%GPQA Diamond88.1%MMLU-Pro86.2%SWE-Bench Verified79%

Browsecomp73.2%

MCP Atlas69%SWE-Bench Pro52.6%SciCode49.9%Toolathlon47.8%Humanity’s Last Exam45.1%

Detail model

Tanggal rilis

30 Jul 2026

Parameter

Not disclosed

Lisensi

Open Weights

Jendela konteks

1,000,000 tokens

Harga input

$0.14/M

Harga output

$0.28/M

Kecepatan output

113 t/s

Waktu ke token pertama

1.34 s

Estimasi tagihan bulanan

Permintaan API bulanan: 100,000Token input rata-rata: 1,500Token output rata-rata: 500Rasio hit cache prompt: 50%

Estimasi pengeluaran bulanan

$0.00

Menghitung penghematan vs GPT-4o…

Kutip & sematkan

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BibTeX

@misc{llmpodium2026deepseekv4flash,
  title = {Benchmark Analysis and Intelligence Evaluation of DeepSeek V4 Flash},
  author = {LLMPodium Research},
  year = {2026},
  url = {https://llmpodium.com/models/deepseek-v4-flash}
}