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DeepSeek Modelle
Entdecken Sie alle 4 Modelle von DeepSeek mit detaillierten Preisen, Vor- und Nachteilen sowie Entwicklerempfehlungen.
4
Modelle
$0.140
Niedrigster Input
1M
Max. Kontext
2
Qualitätsstufen
Schnellempfehlungen
Bestes Preis-Leistungs-Verhältnis: DeepSeek V4 Flash ($0.140/1M)
Beste Qualität: DeepSeek V4 Flash
Am besten für logisches Denken: DeepSeek V4 Pro
DeepSeek V4 Pro
ReasoningDeep reasoning, complex analysis
Wann verwenden: Best budget reasoning model with massive output capacity for math, logic, and analysis.
Upgrade-Highlights
- ◆384K max output — largest in the market (3x GPT-5.5's 128K)
- ◆1M context window — 16x increase over DeepSeek R1's 65K
- ◆99% cheaper than GPT-5.5 for reasoning ($0.435 vs $5/M input)
- ◆Cached input: $0.003625/M — 99.2% savings for repeated prefixes
- ◆Thinking mode: toggleable deep reasoning without extra cost
Input-Preis
$0.435
per 1M tokens
Output-Preis
$0.870
per 1M tokens
Cached Input
$0.0036
per 1M tokens
Batch-Input
—
per 1M tokens
Kontextfenster: 1M
Max. Output: 384,000 tokens
Wissensstand: 2025-06
VisionFunktionsaufrufFeinabstimmungJSON-Modus
Vorteile
- 384K max output — largest available
- 1M context window
- 99% cheaper than GPT-5.5 for reasoning
Nachteile
- No vision support
- No fine-tuning
- Thinking mode adds token overhead
Leistung
Ausgabegeschwindigkeit~30 tok/s
Rate-Limit2,000 RPM
Multimodal
BildeingabeBildausgabeAudioeingabeAudioausgabe
Benchmarks
MMLU
88.0%
AIME 2024
85.0%
SWE-bench Verified
71.0%
MATH
82.5%
DeepSeek V4 Flash
FlagshipUltra-cheap coding, general tasks
Wann verwenden: Best for high-volume coding and general tasks where cost is the primary concern.
Upgrade-Highlights
- ◆Cheapest LLM available: $0.14/M input, $0.28/M output
- ◆1M context + 384K output — same capacity as V4 Pro at 1/3 the price
- ◆Dual mode: thinking and non-thinking — switch based on task complexity
- ◆Cached input: $0.0028/M — 98% savings for system prompts
- ◆No vision — text-only; use GPT-4.1 or Gemini for multimodal needs
Input-Preis
$0.140
per 1M tokens
Output-Preis
$0.280
per 1M tokens
Cached Input
$0.0028
per 1M tokens
Batch-Input
—
per 1M tokens
Kontextfenster: 1M
Max. Output: 384,000 tokens
Wissensstand: 2025-06
VisionFunktionsaufrufFeinabstimmungJSON-Modus
Vorteile
- Cheapest LLM available at $0.14/M input
- 1M context + 384K output
- Supports both thinking and non-thinking modes
Nachteile
- No vision support
- Quality below GPT-5.4 for complex tasks
- No fine-tuning
Leistung
Ausgabegeschwindigkeit~60 tok/s
Rate-Limit5,000 RPM
Multimodal
BildeingabeBildausgabeAudioeingabeAudioausgabe
Benchmarks
MMLU
84.5%
HumanEval
86.0%
SWE-bench Verified
55.0%
DeepSeek V3
FlagshipCoding, math, reasoning
Wann verwenden: Best budget flagship for coding-heavy workloads. 10x cheaper than GPT-4.1 for comparable quality.
Upgrade-Highlights
- ◆10x cheaper than GPT-4.1 ($0.27 vs $2/M input) for comparable coding
- ◆Fine-tuning available — customize for domain-specific coding tasks
- ◆Prompt caching: $0.07/M — 74% savings for repeated system prompts
- ◆671B MoE params with 37B active — flagship intelligence at budget price
- ◆65K context is small vs 1M competitors — upgrade to V4 for long context
Input-Preis
$0.270
per 1M tokens
Output-Preis
$1.10
per 1M tokens
Cached Input
$0.070
per 1M tokens
Batch-Input
—
per 1M tokens
Kontextfenster: 66K
Max. Output: 8,192 tokens
Wissensstand: 2024-07
VisionFunktionsaufrufFeinabstimmungJSON-Modus
Vorteile
- Extremely cheap for flagship quality
- Excellent coding & math
- Fine-tuning + caching available
Nachteile
- Only 65K context
- No vision
- Limited function calling reliability
Leistung
Ausgabegeschwindigkeit~50 tok/s
Rate-Limit3,000 RPM
Multimodal
BildeingabeBildausgabeAudioeingabeAudioausgabe
Benchmarks
MMLU
87.1%
SWE-bench Verified
50.0%
MATH
75.0%
HumanEval
89.0%
DeepSeek R1
ReasoningDeep reasoning, math proofs
Wann verwenden: Budget reasoning model — use when o3 cost is prohibitive for math/logic pipelines.
Upgrade-Highlights
- ◆4x cheaper than o3 ($0.55 vs $2/M input) for comparable reasoning
- ◆AIME 2024: 79.8% — competitive with o1 on math benchmarks
- ◆Prompt caching: $0.14/M — 75% savings for repeated prefixes
- ◆Open-source reasoning model — self-host for unlimited usage
- ◆No function calling or vision — pure reasoning; upgrade to V4 Pro for tools
Input-Preis
$0.550
per 1M tokens
Output-Preis
$2.19
per 1M tokens
Cached Input
$0.140
per 1M tokens
Batch-Input
—
per 1M tokens
Kontextfenster: 66K
Max. Output: 8,192 tokens
Wissensstand: 2024-07
VisionFunktionsaufrufFeinabstimmungJSON-Modus
Vorteile
- 4x cheaper than o3 for reasoning
- Strong math & logic
- Good prompt caching savings
Nachteile
- No function calling
- No vision or fine-tuning
- Only 65K context
Leistung
Ausgabegeschwindigkeit~20 tok/s
Rate-Limit2,000 RPM
Multimodal
BildeingabeBildausgabeAudioeingabeAudioausgabe
Benchmarks
AIME 2024
79.8%
MATH
97.3%
GPQA
71.5%
Nebeneinander-Vergleich
| Modell | Stufe | Input | Output | Kontext |
|---|---|---|---|---|
| DeepSeek V4 Pro | Reasoning | $0.435 | $0.870 | 1M |
| DeepSeek V4 Flash | Flagship | $0.140 | $0.280 | 1M |
| DeepSeek V3 | Flagship | $0.270 | $1.10 | 66K |
| DeepSeek R1 | Reasoning | $0.550 | $2.19 | 66K |