DeepSeek V3.1
DeepSeek V3.1 ist ein starkes Reasoning-Model mit sehr gutem Preis-Leistungs-Verhältnis — inklusive optionalem Enhanced Thinking Mode für komplexe Probleme.
Overview
| Property | Value |
|---|---|
| Provider | DeepSeek |
| Cost | 10 credits |
| Modality | Text |
| Vision | ❌ No |
| Prompt Required | Yes |
What It's Best For
- Cost-effective reasoning — Gute Resultate zu etwa halbem Preis im Vergleich zu Premium Models
- Technical tasks — Code generation, debugging, analysis
- Structured outputs — JSON, Tabellen und formatierte Daten
- General assistance — Vielseitig über viele Use Cases
- Enhanced reasoning — Optionaler Thinking Mode für komplexe Probleme
Inputs
Prompt (Required)
Der Haupt-Textinput, der beschreibt, was das Model tun soll.
Connection Color: 🟡 Yellow
Configuration
Thinking Mode
Type: Select
Enhanced reasoning für komplexe Probleme aktivieren.
| Option | Description |
|---|---|
| None | Standard fast responses |
| Medium (Enhanced Reasoning) | Deeper analysis, step-by-step thinking |
Default: None
When to use Medium:
- Multi-step math problems
- Complex logic puzzles
- Detailed code analysis
- Strategic planning tasks
Max Tokens
Type: Slider
Range: 1 - 4,096
Default: 1,024
Maximale Token-Anzahl.
Temperature
Type: Slider
Range: 0 - 2
Default: 0.1
Steuert Randomness. Der niedrige Default (0.1) macht DeepSeek standardmäßig deterministischer.
Top P
Type: Slider
Range: 0 - 1
Default: 1
Nucleus sampling für Response Diversity.
Presence Penalty
Type: Slider
Range: -2 to 2
Default: 0
Penalisiert Tokens, die schon vorkamen. Positive Werte fördern neue Themen.
Frequency Penalty
Type: Slider
Range: -2 to 2
Default: 0
Penalisiert Tokens nach Häufigkeit. Positive Werte reduzieren Wiederholungen.
Output
Type: Text
Connection Color: 🟡 Yellow
Use Cases
Code Generation
Write a Python function that validates email addresses using regex.
Include error handling and docstrings.
Data Transformation
Convert this CSV data into a properly formatted JSON structure
with nested objects for related fields.
Technical Documentation
Write API documentation for this endpoint including request/response
examples, error codes, and rate limiting information.
Enhanced Reasoning Task
With Thinking Mode: Medium
A company has three products. Product A costs $10 and sells 100 units.
Product B costs $15 and sells 80 units. Product C costs $20 and sells 50 units.
If they want to increase total revenue by 20% while keeping prices fixed,
what's the minimum increase in units needed for each product?
Tips for Best Results
- Use low temperature — DeepSeek funktioniert gut mit deterministischen Settings
- Enable thinking for complex tasks — Lohnt sich für komplexe Aufgaben
- Be structured — Klare, organisierte Prompts liefern bessere Outputs
- Leverage for technical work — Exzellent für Code und Daten
- Iterate quickly — Geringe Kosten erlauben mehr Experimentieren
Cost Comparison
| Model | Cost | Best For |
|---|---|---|
| Llama 3 8B | 2 credits | Simple tasks |
| DeepSeek V3.1 | 10 credits | Balanced performance |
| Gemini 2.5 Flash | 10 credits | Multimodal tasks |
| GPT-5 | 20 credits | Maximum quality |
| Claude 4.5 Sonnet | 30 credits | Long-form writing |
DeepSeek V3.1 bietet sehr gutes Value für Text-only Tasks ohne Vision Requirements.
Related Models
- Llama 3 8B — Noch günstiger für simple Tasks
- Llama 3 70B — Stärker, etwas teurer
- GPT-5 — Premium Option mit Vision