DeepSeek-V3.1-Terminus builds on its predecessor with key updates that improve reliability and efficiency. This model addresses past issues while excelling in practical tasks.
It focuses on fixing language inconsistencies and boosting agent features for everyday use.
Key Improvements in DeepSeek-V3.1-Terminus
DeepSeek-V3.1-Terminus tackles earlier problems with language mixing in responses, ensuring smooth outputs in English, Chinese, or mixed setups. This change helps teams working across languages.
The model enhances agent capabilities too. For instance:
- Code agent now handles debugging and generation more accurately
- Search agent retrieves and synthesizes web information faster
- Tool integration works seamlessly with external services for complex tasks
These updates make it ideal for automated workflows.
Technical Details and Performance
DeepSeek-V3.1-Terminus uses a setup with 671 billion total parameters but only 37 billion active per token. This design supports up to 128,000 tokens, making it efficient for long documents.
In benchmarks, it scores high:
- 85.0 on MMLU-Pro for knowledge tests
- 80.7 on GPQA-Diamond for advanced queries
- 96.8 on SimpleQA for straightforward answers
- Improvements in areas like BrowseComp from 30.0 to 38.5
These results show gains in practical scenarios, with faster responses than previous versions.
Pricing and Value
Pricing is a standout feature. Input tokens cost as low as $0.07 per million for cache hits and $0.56 for cache misses. Output tokens are $1.68 per million.
Compare that to:
| Model | Input Cost (per 1M) | Output Cost (per 1M) |
|------------------------|----------------------|----------------------|
| DeepSeek-V3.1-Terminus | $0.56 | $1.68 |
| GPT-4 Turbo | $10.00 | $30.00 |
| Claude 4.1 Opus | $15.00 | $75.00 |
This offers up to 120 times the savings, making it accessible for startups and enterprises.
Real-World Applications
In software development, it aids in:
- Generating code in various languages
- Debugging with precise suggestions
- Reviewing code and creating documentation
For businesses, it supports:
- Automating customer support responses
- Analyzing data for insights
- Handling multi-step processes
In research, it helps with:
- Summarizing papers
- Interpreting datasets
- Forming hypotheses
As an open-source option under MIT license, it's easy to deploy locally for privacy and customization.
Getting Started and Limitations
To begin, sign up for the API or download weights from Hugging Face. Use chat mode for quick interactions and reasoner mode for detailed tasks.
Keep in mind potential limits:
- It works best with English and Chinese
- Context is capped at 128,000 tokens
- May not excel in multimodal tasks where other models shine
Why Choose DeepSeek-V3.1-Terminus
This model delivers strong performance at a low cost, with features that support real needs. Its open-source nature adds flexibility for long-term projects.
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