deepseek-chat The deepseek-chat model has been upgraded to DeepSeek-V2-0628. Model's reasoning capabilities have improved, as shown in relevant benchmarks: Coding: HumanEval Pass@1 79.88% -> 84.76% Mathematics: MATH ACC@1 55.02% -> 71.02% Reasoning: BBH 78.56% -> 83.40% In the Arena-Hard evaluation, the win rate against GPT-4-0314 increased from 41.6% to 68.3%. The model's role-playing capabilities have significantly enhanced, allowing it to act as different characters as requested during conversations.
deepseek-chat The deepseek-chat model has been upgraded to DeepSeek-V2-0628. Model's reasoning capabilities have improved, as shown in relevant benchmarks: Coding: HumanEval Pass@1 79.88% -> 84.76% Mathematics: MATH ACC@1 55.02% -> 71.02% Reasoning: BBH 78.56% -> 83.40% In the Arena-Hard evaluation, the win rate against GPT-4-0314 increased from 41.6% to 68.3%. The model's role-playing capabilities have significantly enhanced, allowing it to act as different characters as requested during conversations.
deepseek-coder & deepseek-chat Upgraded to DeepSeek V2.5 Model The DeepSeek V2 Chat and DeepSeek Coder V2 models have been merged and upgraded into the new model, DeepSeek V2.5. For backward compatibility, API users can access the new model through either deepseek-coder or deepseek-chat . The new model significantly surpasses the previous versions in both general capabilities and code abilities. The new model better aligns with human preferences and has been optimized in various areas such as writing tasks and instruction following: ArenaHard win rate improved from 68.3% to 76.3% AlpacaEval 2.0 LC win rate increased from 46.61% to 50.52% MT-Bench score rose from 8.84 to 9.02 AlignBench score increased from 7.88 to 8.04 The new model has further enhanced its code generation capabilities based on the original Coder model, optimized for common programming application scenarios, and achieved the following results on the standard test set: HumanEval: 89% LiveCodeBench (January-September): 41%
deepseek-coder The deepseek-coder model has been upgraded to DeepSeek-Coder-V2-0614, significantly enhancing its coding capabilities. It has reached the level of GPT-4-Turbo-0409 in code generation, code understanding, code debugging, and code completion. Additionally, it possesses excellent mathematical and reasoning abilities, and its general capabilities are on par with DeepSeek-V2-0517.