DeepSeek V4-Flash — Spezifikationen
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Entwickler | DeepSeek |
|---|---|
| Typ | LLM (MoE) |
| Modality | Text → Text |
| Parameter | 284 Mrd. insgesamt / ~13 Mrd. aktiv (MoE) |
| Kontextfenster | 1 Mio. |
| Maximale Ausgabe | 384 K |
| Lizenz | MIT (offen) |
| Offene Gewichte | Ja |
| Veröffentlicht | 2026-04 |
| Eingabepreis | $0.14 /1M |
| Ausgabepreis | $0.28 /1M |
| API-Anbieter | DeepSeek, OpenRouter |
Lokal ausführen
| VRAM (4-Bit) | ~140 GB |
|---|---|
| Mindest-GPU | 2× H100 80 GB (4-Bit) |
What is DeepSeek V4-Flash?
DeepSeek V4-Flash is the lighter member of the DeepSeek V4 family — 284B total parameters
with roughly 13B active per token, a 1M-token context window, and open MIT weights. At $0.14
in / $0.28 out per million tokens it is priced for high-volume use, and it is one of the
strongest capability-per-dollar options anywhere in the market.
The number worth internalising is the blended rate of about $0.17 per million tokens
against a frontier model’s $10. That is a ~60× spread for a model that still scores in the
respectable middle of the intelligence rankings, which makes V4-Flash the obvious candidate
for any workload where volume matters more than peak reasoning: bulk classification,
document processing, first-pass summarisation, synthetic data generation, and the retrieval
layer of a RAG pipeline. The 1M context at that price is close to unmatched. Self-hosting is
possible but not casual — about 140 GB of VRAM at 4-bit, so two H100 80GBs — which for most
teams means the API is the practical route and the open weights are insurance rather than a
deployment plan.
DeepSeek V4-Flash pricing: API cost per 1M tokens
| Eingabe (pro 1 Mio. Token) | $0.140 |
|---|---|
| Ausgabe (pro 1 Mio. Token) | $0.280 |
| Verhältnis Output/Input | 2× |
| Gemischt (4:1 Input:Output) | $0.168 pro 1 Mio. Tokens |
What DeepSeek V4-Flash costs per month
Tatsächliche monatliche Ausgaben bei einem 4:1-Input-zu-Output-Mix – dem Verhältnis, das typische Chat- oder RAG-Arbeitslasten tatsächlich erzeugen.
| Workload | Tokens/Monat | Kosten pro Monat |
|---|---|---|
| Nebenprojekt | 1 Mio. Eingabe / 0,25 Mio. Ausgabe | $0.21 |
| Kleines Team | 20 Mio. Eingabe / 5 Mio. Ausgabe | $4.20 |
| Produktion | 200 Mio. Eingabe / 50 Mio. Ausgabe | $42 |
Stellen Sie Ihre eigenen Berechnungen im KI-API-Kostenrechner.
Cheaper alternatives to DeepSeek V4-Flash
| Modell | Gewichteter Preis pro Million US-Dollar | Sie sparen |
|---|---|---|
| Mistral 7B offenere | $0.0220 | 87% cheaper |
| Llama 3.1 8B offenere | $0.0220 | 87% cheaper |
| Mistral NeMo 12B offenere | $0.0240 | 86% cheaper |
Selbst hosten oder die API nutzen?
DeepSeek V4-Flash is open-weight, so you can run it yourself. It needs ~140 GB of VRAM at 4-bit (2× H100 80GB (4-bit)). Self-hosting only beats the API once your volume is high enough to keep that hardware busy — the Selbsthosting vs. API-Rechner berechnet den Break-even-Punkt für Ihr Token-Volumen.
Häufig gestellte Fragen
How much does DeepSeek V4-Flash cost per 1M tokens?
DeepSeek V4-Flash costs $0.140 per 1M input tokens and $0.280 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $0.168 per 1M tokens.
How much does DeepSeek V4-Flash cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $4.20 on DeepSeek V4-Flash. A side project (1M in / 0.25M out) costs roughly $0.21.
What is a cheaper alternative to DeepSeek V4-Flash?
Mistral 7B is the strongest cheaper option in our database at $0.0220 per 1M blended — about 87% less than DeepSeek V4-Flash. It is also open-weight, so self-hosting is an option.
Can I run DeepSeek V4-Flash locally?
Yes. DeepSeek V4-Flash is open-weight and needs about ~140 GB of VRAM at 4-bit quantisation (2× H100 80GB (4-bit)).
Why does DeepSeek V4-Flash charge more for output than input?
Output tokens are generated one at a time and cannot be batched the way a prompt can, so they cost the provider more to serve. DeepSeek V4-Flash charges 2× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.
See every DeepSeek model priced side by side: DeepSeek-API-Preismodell.
Die Preise entsprechen den offiziell veröffentlichten Listenpreisen für die primäre API des jeweiligen Modells und werden regelmäßig aktualisiert, sobald Anbieter diese ändern. Volumen-, Batch- und Cached-Input-Rabatte sind nicht enthalten. Vergleichen Sie alle Modelle nebeneinander im Datenbank für KI-Modelle oder das LLM-Leaderboard.