Compare the performance of DeepSeek V3 API, Claude 3.5 Sonnet, and GPT-4o across various tasks to understand their distinct strengths and limitations.
This comparison examines the DeepSeek V3 API and Claude 3.5 Sonnet, analyzing their technical architectures, performance capabilities, and practical applications:
DeepSeek V3 vs Claude 3.5 Sonnet
characteristic | DeepSeek V3 | Claude 3.5 Sonnet |
Parameter size | 671 billion total parameters, only 37 billion parameters per token enabled (Mixture-of-Experts architecture) | Not explicitly mentioned, but known for efficient processing and optimized performance |
Core technology architecture | Mixture-of-Experts (MoE) + Multi-head Latent Attention (MLA) to improve contextual understanding and reasoning | Enhanced reasoning and context retention with visual data analysis capabilities (e.g., chart and graph interpretation) |
Reasoning and language comprehension | Efficient handling of complex reasoning, multi-language support, and 87.1% MMLU benchmark | Excellent performance on GPQA (Graduate-Level Reasoning) and MMLU (Undergraduate-Level Knowledge) benchmarks |
Coding ability | Supports multi-language coding, error detection, code optimization, and outstanding performance in competition coding | The coding success rate is increased to 64%, and the code can be automatically generated, edited, and executed, which is suitable for the whole life cycle of software development |
Visual data processing | There is no specific mention of visual processing capabilities | Supports the extraction of information from charts, complex graphs, and is suitable for data analysis and scientific tasks |
Context window size | Not explicitly mentioned | Supports up to 4096 tokens context windows for long text processing |
Performance benchmarking | Excellent performance in multiple benchmarks, such as BBH (87.5%) and mathematical reasoning tasks | Surpasses GPT-4 in several benchmarks, such as coding, human assessment, etc |
Application scenarios | Chatbots, educational tools, content generation, coding assistance, and other multi-domain applications | It is suitable for diverse application scenarios such as knowledge question answering platform, visual data extraction, and automated process |
Deployment flexibility | It supports local inference and cloud deployment, and is compatible with NVIDIA, AMD GPUs, and Huawei Ascend NPUs | Accessible through platforms such as the Anthropic API, Amazon Bedrock, and Google Cloud Vertex AI |
Training efficiency | Using the FP8 mixed-precision training framework, the cost was only $5.5 million, and the training took about 2.788M H800GPU hours | The cost of training is not clearly disclosed, but it is known for its efficient performance and cost-effectiveness |
- The advantage of DeepSeek V3 is the efficiency and flexibility brought by its Mixture-of-Experts architecture, especially in multi-language support and complex inference, while at a very competitive training cost.
- Claude 3.5 Sonnet is known for its enhanced visual processing capabilities, larger context windows, and application capabilities throughout the software development lifecycle, especially for scenarios that require the integration of visual data analysis.
Choosing the right model for your needs will depend on the specific use case, for example, Claude 3.5 Sonnet can be preferred for visual data processing, and DeepSeek V3 can be selected for multi-language support or efficient inference.
The pricing difference between DeepSeek-V3 and o1 is significant:
Enter pricing
- DeepSeek-V3: Only $0.14 per million tokens
- O1: $15.00 per million tokens
Output pricing
- DeepSeek-V3: Only $0.28 per million tokens
- O1: $60.00 per million tokens
Cost comparison
The price of DeepSeek-V3 is about 178.6 times cheaper than that of O1. This huge price difference gives DeepSeek-V3 a significant cost advantage in large-scale application scenarios.
Pricing features:
- DeepSeek-V3 has a more affordable pricing strategy for applications that require a lot of text-intensive processing
- o1 offers a larger output limit despite being more expensive (100K tokens vs 8K tokens of DeepSeek-V3)
Here's a comparison table of the DeepSeek V3 API with Claude 3.5 Sonnet, GPT-4o, o1, o1 Mini, Gemini 2.0, and Grok-2:
characteristic | DeepSeek V3 | Claude 3.5 Sonnet | GPT-4o | o1 | o1 Mini | Gemini 2.0 | Grok-2 |
The number of parameters | 671B (37B enabled per token) | Undisclosed | Undisclosed | Undisclosed | Undisclosed | Undisclosed | Undisclosed |
Architecture | Mixture of Experts (256 experts) | Undisclosed | Undisclosed | Undisclosed | Undisclosed | Undisclosed | Undisclosed |
Context window size | 128K | 200K | 128K | 100K | 100K | Undisclosed | Undisclosed |
Enter the price ($/million tokens) | $0.14 | $3.00 | $2.50 | $15.00 | $7.50 | Undisclosed | Undisclosed |
Output Price ($/million tokens) | $0.28 | $15.00 | $10.00 | $60.00 | $30.00 | Undisclosed | Undisclosed |
Maximum output tokens | 8K | Undisclosed | 16.4K | 100K | 100K | Undisclosed | Undisclosed |
Open source | be | not | not | not | not | not | not |
Processing speed (tokens/s) | About 65 | 3 times faster than Claude 2 Opus | About 77.4 | Not provided | Not provided | Not provided | Not provided |
Key Points :
- DeepSeek V3 is priced at the most cost-effective of all models, especially in large-scale use cases.
- Claude 3.5 Sonnet and GPT-4o offer a larger context window but are more expensive.
- O1 vs O1 Mini offers a larger output token limit, but is expensive.
- DeepSeek V3 is the only open-source model for developers to customize their applications.
Here's a detailed comparison of the DeepSeek V3 API with Claude 3.5 Sonnet, GPT-4o, and o1:
characteristic | DeepSeek V3 | Claude 3.5 Sonnet | GPT-4o | o1 |
Parameter size | 671B (37B enabled per token) | Undisclosed | Undisclosed | Undisclosed |
Architecture | Mixture-of-Experts (MoE) | Undisclosed | Undisclosed | Undisclosed |
Context window size | 128K tokens | 200K tokens | 128K tokens | 100K tokens |
Maximum output tokens | 8K tokens | 8,192 tokens | 16.4K tokens | 100K tokens |
Open source | be | not | not | not |
Cost of input ($/million tokens) | $0.14 | $3.00 | $2.50 | $15.00 |
Cost of Output ($/million tokens) | $0.28 | $15.00 | $10.00 | $60.00 |
Inference speed (tokens/s) | About 65 | About 72.4 | About 77.4 | Undisclosed |
Performance Benchmarking (MMLU) | 88.5% | 88.3% | 88.7% | Undisclosed |
Code Generation Capabilities (HumanEval) | 82.6% pass@1 | 92% pass@1 | 90.2% pass@1 | Undisclosed |
Mathematical Ability (MATH) | 61.6% | 71.1% | 75.9% | Undisclosed |
Key differences:
- Price & Cost-Effectiveness:
- DeepSeek V3 is the most competitively priced, with input and output tokens costing $0.14 and $0.28, respectively, which is much lower than other models.
- The price of Claude 3.5 Sonnet and GPT-4o is significantly higher, especially the cost of output tokens.
- Context Window and Output Limitations:
- Claude offers the largest contextual window (200K tokens) and is suitable for handling very long texts.
- GPT-4o supports a larger single-output limit (16.4K tokens), while o1 reaches a staggering 100K tokens.
- Performance and Application Scenarios:
- DeepSeek V3 excels in inference and math benchmarks, making it ideal for applications that require efficient inference and cost control.
- Claude is a leader in code generation and creative writing, which is suitable for technical development and content creation.
- GPT-4o is stable in terms of overall performance, but the price is on the high side compared to DeepSeek.
Suggestion:
- If you need cost-effectiveness, open-source flexibility, and powerful inference capabilities, DeepSeek V3 is the best choice.
- If your application requires processing very long text or code generation, Claude or GPT-4o are more suitable, but the cost needs to be higher.
- O1 is suitable for very large output needs, but its high price limits its universal application.
Here's a price comparison table of the DeepSeek V3 API with Claude 3.5 Sonnet, GPT-4o, o1, o1 Mini, Gemini 2.0, and Grok-2:
model | Cost of input ($/million tokens) | Cost of Output ($/million tokens) | Context Window Size (Tokens) | Maximum output tokens | Open source |
DeepSeek V3 | $0.14 | $0.28 | 128K | 8K | be |
Claude 3.5 Sonnet | $3.00 | $15.00 | 200K | Undisclosed | not |
GPT-4o | $2.50 | $10.00 | 128K | 16.4K | not |
o1 | $15.00 | $60.00 | 100K | 100K | not |
o1 Mini | $3.00 | $12.00 | 128K | Undisclosed | not |
Gemini 2.0 | $0.075 | $0.30 | 128K | Undisclosed | not |
Grok-2 | $2.00 | $10.00 | 131K | Undisclosed | not |
- Price Difference:
- DeepSeek V3 is the most competitive in price, with input and output token costs of $0.14 and $0.28, respectively, which is much lower than other models.
- Gemini 2.0 also has a relatively low input cost ($0.075) but a slightly higher output cost ($0.30).
- The O1 series models (including the O1 and O1 Mini) are significantly more expensive, especially the O1 output token costs up to $60.
- Context Window and Output Limitations:
- Claude 3.5 Sonnet offers the largest context window (200K tokens) and is suitable for handling very long texts.
- o1 supports the maximum single output limit (100K tokens), which is suitable for scenarios that require a large amount of generation.
- Open Source:
- DeepSeek V3 is the only open-source model for developers to customize their applications.
Summarizing Recommendations:
- If you need cost-effectiveness and flexibility, DeepSeek V3 is the best choice.
- If the application requires handling very long texts or greater generation capacity, the Claude or o1 series is more suitable, but the higher cost needs to be considered.
- Gemini 2.0 offers a low-cost option, but the features may not be as comprehensive as other models.