deepseek-coder Model Card
by Deepseek
Explore detailed LLM evaluation metrics and benchmarks for deepseek-coder, a proprietary large language model by Deepseek. Compare API costs, context windows, and performance across multiple LLM benchmarks including MMLU (general knowledge), MMMU (multimodal capabilities), HellaSwag (common sense reasoning), HumanEval (code generation), and MATH (mathematical reasoning).
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Pricing
Input Processing
Cost per million tokens for processing prompts
$0.14per million tokens
Generation
Cost per million tokens for responses
$0.28per million tokens
Model Details
Context Length
Maximum input length the model can process at once
Not available
Response Length
Maximum length of a single generated response
Not available
Release Date
First public release date
Not specified
Training Cutoff
Latest date of data included in training
Not specified
License Type
Model licensing and availability
Proprietary
Performance Metrics
General Knowledge (MMLU)
Accuracy on diverse academic and real-world topics
Not available
Multimodal Tasks (MMMU)
Performance on tasks combining text, images, and other media
Not available
Common Sense (HellaSwag)
Understanding of everyday scenarios and situations
Not available
Code Generation (HumanEval)
Ability to write and understand programming code
Not available
Mathematical Ability (MATH)
Accuracy in mathematical computations and reasoning
Not available
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Next.js 14, TypeScript & Tailwind
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