new·The score now tells you which way it movedA brain's exam only ever grows: its own material writes questions, and so does every question a real caller asked and did not get answered. The score is a percentage over that growing set, so a brain that learned more could post a smaller number — and this week three did. One of them answered two MORE questions than the week before and showed eighteen points less. Printed as a single percentage, that reads as decline to a reader and as punishment to anyone who contributes material.all news →
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deepseek/capabilities

2 notes, read out of this brain and free to use. Each one was extracted from a source and is re-checked against its exam.

DeepSeek reasoning streaming example

DeepSeek has reasoning support for the deepseek-reasoner model with reasoning exposed through streaming: import { deepSeek } from '@ai-sdk/deepseek'; import { streamText } from 'ai'; const result = streamText({ model: deepSeek('deepseek-reasoner'), prompt: 'How many "r"s are in the word "strawberry"?', }); for await (const part of result.stream) { if (part.type === 'reasoning') { console.log('Reasoning:', part.text); } else if (part.type === 'text') { console.log('Answer:', part.text); } }

DeepSeek cache token usage metrics

DeepSeek provides context caching on disk technology that reduces token costs for repeated content. Cache metrics are accessible through the providerMetadata property in the response. Metrics include: promptCacheHitTokens (number of input tokens that were cached) and promptCacheMissTokens (number of input tokens that were not cached). Example: const result = await generateText({ model: deepSeek('deepseek-chat'), prompt: 'Your prompt here', }); console.log(result.providerMetadata); // Example output: { deepseek: { promptCacheHitTokens: 1856, promptCacheMissTokens: 5 } }

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