DeepSeek AI by APIpie: Overview & Key Features
For detailed information about using models with APIpie, check out our Models Overview and Completions Guide.
Description
The DeepSeek Series represents DeepSeek AI's family of state-of-the-art large language models. These models leverage cutting-edge technology including Mixture-of-Experts (MoE) architecture to deliver exceptional performance in natural language processing, code generation, mathematical reasoning, and extended-context interactions. The models are available through various providers integrated with APIpie's routing system.
Key Features
- Extended Token Capacity: Models support context lengths from 32K to 131K tokens for handling various text processing needs.
- Multi-Provider Availability: Accessible across platforms like OpenRouter, Together, and Amazon Bedrock.
- Diverse Applications: Optimized for chat, instruction-following, analysis, writing, code generation, and mathematical reasoning.
- Mixture-of-Experts Architecture: DeepSeek-V3 and DeepSeek-R1 utilize MoE architecture with 671B total parameters and 37B activated parameters for efficient inference.
- Open Source Models: DeepSeek offers MIT-licensed models that support commercial use, including distilled versions based on Llama and Qwen.
Model Comparison and Monitoring
When choosing between DeepSeek models, APIpie provides comprehensive monitoring tools to help make informed decisions:
Performance Monitoring:
- Real-time availability tracking across providers (OpenRouter, Together, Bedrock)
- Latency metrics and historical performance data
- Response time comparisons between different model versions
Pricing & Cost Analysis:
- Live pricing updates through our Models Route & Dashboard
- Cost comparisons and pricing trends across different providers
- Usage-based cost optimization recommendations
Health Metrics:
- Global AI health dashboard for real-time status
- Provider reliability tracking
- Model uptime statistics
This monitoring system helps users:
- Compare costs and pricing across different DeepSeek models and providers
- Track performance metrics to optimize response times
- Make data-driven decisions based on availability and reliability
- Monitor system health and anticipate potential issues
Use the Models Route to access real-time pricing and performance data for all DeepSeek models.
Model List in the DeepSeek Series
Model List updates dynamically please see the Models Route for the up to date list of models
DeepSeek-V3 is a strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token. DeepSeek-R1 is built on the same architecture but focuses on enhanced reasoning capabilities through reinforcement learning. The DeepSeek-R1-Distill series offers smaller, efficient models that maintain strong performance, especially on mathematical and coding tasks.
| Model Name | Max Tokens | Response Tokens | Provider | Type |
| deepseek-chat | 64,000 | 16,000 | OpenRouter | LLM |
| DeepSeek-V3 | 131,072 | 131,072 | Together | LLM |
| deepseek-r1-distill-llama-8b | 32,000 | 32,000 | OpenRouter | LLM |
| deepseek-r1-distill-qwen-1.5b | 131,072 | 32,768 | OpenRouter | LLM |
| deepseek-r1-distill-qwen-14b | 64,000 | 64,000 | OpenRouter | LLM |
| deepseek-r1-distill-qwen-32b | 131,072 | 8,192 | OpenRouter | LLM |
| deepseek-r1-distill-llama-70b | 131,072 | 8,192 | OpenRouter | LLM |
| deepseek-r1 | 64,000 | 16,000 | OpenRouter | LLM |
| r1-v1 | - | - | Bedrock | LLM |
Example API Call
Below is an example of how to use the Chat Completions API to interact with a model from the DeepSeek Series, such as deepseek-chat.
curl -L -X POST 'https://apipie.ai/v1/chat/completions' \
-H 'Content-Type: application/json' \
-H 'Accept: application/json' \
-H 'Authorization: Bearer <YOUR_API_KEY>' \
--data-raw '{
"provider": "openrouter",
"model": "deepseek-chat",
"max_tokens": 150,
"messages": [
{
"role": "user",
"content": "Can you explain how photosynthesis works?"
}
]
}'
Response Example
The expected response structure for the DeepSeek model might look like this:
{
"id": "chatcmpl-12345example12345",
"object": "chat.completion",
"created": 1729535643,
"provider": "openrouter",
"model": "deepseek-chat",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Photosynthesis is the process by which plants convert sunlight into chemical energy. Here's how it works:\n\n1. **Light Absorption**: Plants capture sunlight using chlorophyll in their leaves\n\n2. **Water and CO2**: They take in water through roots and carbon dioxide through leaf pores\n\n3. **Chemical Reaction**: Using sunlight's energy, they convert H2O and CO2 into glucose and oxygen:\n 6CO2 + 6H2O + light → C6H12O6 + 6O2\n\nThis process produces food for the plant and releases oxygen as a byproduct."
},
"logprobs": null,
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 15,
"completion_tokens": 125,
"total_tokens": 140,
"prompt_characters": 45,
"response_characters": 520,
"cost": 0.000107,
"latency_ms": 2243
},
"system_fingerprint": "fp_123abc456def"
}
API Highlights
- Provider: Specify the provider or leave blank for automatic selection.
- Model: Use any model from the DeepSeek Series suited to your task. See Models Guide.
- Max Tokens: Set the maximum response token count (e.g., 150 in this example).
- Messages: Format your request with a sequence of messages, including user input and system instructions. See message formatting.
This example demonstrates how to seamlessly query models from the DeepSeek Series for conversational or instructional tasks.
DeepSeek Model Variants
DeepSeek-V3
DeepSeek-V3 is a powerful Mixture-of-Experts (MoE) language model with 671B total parameters and 37B activated for each token. Pre-trained on 14.8 trillion diverse and high-quality tokens, it outperforms other open-source models and achieves performance comparable to leading closed-source models.
Key Features:
- Innovative load balancing strategy without auxiliary loss
- Multi-Token Prediction (MTP) training objective
- FP8 mixed precision training framework
- 128K context window support
- Exceptional performance on math, code, and reasoning tasks
DeepSeek-R1
DeepSeek-R1 is built on the same architecture as DeepSeek-V3 but focuses on enhanced reasoning capabilities through reinforcement learning. It achieves performance comparable to leading models on math, code, and reasoning tasks.
Key Features:
- Trained via large-scale reinforcement learning
- Naturally emerged reasoning behaviors including self-verification and reflection
- Strong performance on mathematical reasoning and coding tasks
- MIT license allowing commercial use and distillation
DeepSeek-R1-Distill Series
The DeepSeek-R1-Distill series offers smaller, efficient models that maintain strong performance, especially on mathematical and coding tasks. These models are distilled from DeepSeek-R1 and based on Llama and Qwen architectures.
Available Models:
- DeepSeek-R1-Distill-Qwen-1.5B
- DeepSeek-R1-Distill-Qwen-7B
- DeepSeek-R1-Distill-Llama-8B
- DeepSeek-R1-Distill-Qwen-14B
- DeepSeek-R1-Distill-Qwen-32B
- DeepSeek-R1-Distill-Llama-70B
Applications and Integrations
- Conversational AI: Powering chatbots, virtual assistants, and other dialogue-based systems. Try it with LibreChat or OpenWebUI.
- Code Generation: Leveraging DeepSeek's strong coding capabilities for software development, debugging, and code explanation.
- Mathematical Reasoning: Using DeepSeek-R1 and its distilled models for complex mathematical problem-solving and education.
- Content Creation: Using DeepSeek's writing abilities for content generation and editing.
- Extended Context Tasks: Processing long documents with models supporting up to 131K tokens. Learn more in our Models Guide.
- Educational Support: Providing detailed explanations and tutoring across various subjects, especially in STEM fields.
Ethical Considerations
DeepSeek models are built with responsible AI principles in mind. Users should implement appropriate safeguards and consider potential biases in model outputs. For guidance on responsible AI usage, refer to DeepSeek's documentation and best practices.
Licensing
The DeepSeek Series is available through various API platforms. DeepSeek-V3, DeepSeek-R1, and the DeepSeek-R1-Distill series are licensed under the MIT License, which supports commercial use and allows for modifications and derivative works, including distillation for training other LLMs. For detailed licensing information, consult DeepSeek's documentation and respective hosting providers.
Try out the DeepSeek models in APIpie's various supported integrations.