DeepSeek

DeepSeek V4.1 FlashTerbuka

DeepSeek V4.1 Flash is an open-weights MoE reasoning model with 552B total (16B active) parameters, 1.0M context, and chain-of-thought problem solving.

#379dirilis 10 Sep 2026·Open Weights·552B (16B active)
textimage1.0M ctxpenalaran
Penyedia APIDapatkan Kunci API →Peringkat
Inteligensi
54.5 #379
AAQI 40.0
Kecepatan output
214 t/s
TTFT 1.21 s · ITL 4.7 ms/tok
Harga gabungan (3:1)
$0.18 /1M
Input $0.3/M · Output $1.2/M
Konteks
1.0M
≈ 2,500 halaman A4 · output maks 32,768

Quality Domain Radar

6-Axis Frontier Evaluation vs Category Average & Flagship

DeepSeek V4.1 Flash
Claude Mythos Preview (#1)
Average (68)
Coding (52)Mathematics (68)Hard Science (GPQA) (58)Agentic & Tool Use (48)Knowledge (MMLU) (46)Vision / Multimodal (50)

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

Kelebihan & Trade-off

Di mana ia menang

  • Open weights — self-host, fine-tune and audit with no vendor lock-in
  • 1.0M context — swallows whole repos, codebases or corpora in one pass
  • 214 tok/s output — fast enough for real-time agents
  • Very low blended price — $0.18/1M mixed tokens

Kasus Penggunaan Killer

Deep research
Synthesis across broad knowledge domains with citation-grade recall.
Math & proof work
Step-verified reasoning for olympiad math, theorem proving and formal verification.
SWE-bench agents
Issue-to-PR resolution across multi-file repos — refactor, test and verify autonomously.

Quickstart Developer & API

Atur DEEPSEEK_API_KEY dulu — dapatkan kunci API
curl https://api.deepseek.com/v1/chat/completions \
  -H "Authorization: Bearer $DEEPSEEK_API_KEY" \
  -H "content-type: application/json" \
  -d '{
    "model": "deepseek-v4-1-flash",
    "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
Dense · 552B (16B active)
  • Switchable reasoning effort — trading latency and tokens for accuracy on hard problems.
  • Prompt caching supported — cached input reads at $0.03/1M tokens.
Tanggal rilis
10 Sep 2026
Arsitektur
Dense · 552B (16B active)
Parameter
552B (16B active)
Lisensi
Open Weights
Jendela konteks
1,000,000 tokens
Output maks
32,768 tokens
Modalitas
text + image
Harga cache
baca $0.03 · tulis $0.35 /1M
Penalaran
Level effort
Harga input
$0.3/M
Harga output
$1.2/M
Kecepatan output
214 t/s
Waktu ke token pertama
1.21 s
Data diperbarui
12 Sep 2026

Estimasi tagihan bulanan

Estimasi pengeluaran bulanan
$0.00
Menghitung penghematan vs GPT-4o…

Kutip & sematkan

Badge Markdown GitHub
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BibTeX
@misc{llmpodium2026deepseekv41flash,
  title = {Benchmark Analysis and Intelligence Evaluation of DeepSeek V4.1 Flash},
  author = {LLMPodium Research},
  year = {2026},
  url = {https://llmpodium.com/models/deepseek-v4-1-flash}
}

Sematkan Lencana Skor

Tambahkan lencana Podium Score langsung ke README GitHub atau Hugging Face Anda — menautkan ke peringkat langsung.

Pratinjau
DeepSeek V4.1 Flash LLMPodium Score
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