We partnered with @lmarena_ai to evaluate Grok 4 Fast on both Search and Text Arena, achieving #1 and #8 respectively.
LLMS
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Grok 4 Fast: New Multimodal Model with 2M Context Window
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Introducing Grok 4 Fast, a multimodal reasoning model with a 2M context window that sets a new standard for cost-efficient intelligence. Available for free on http://
grok.com, http://
grok.x.com, iOS and Android apps, and OpenRouter. -
Grok 4 Fast Achieves New Pareto Intelligence Frontier Record
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Grok 4 Fast sets a new record on the Pareto Intelligence frontier as reported by @ArtificialAnlys
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10 Ways Claude Outperforms ChatGPT for Productivity
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Claude is a productivity powerhouse if you know how to use it right. Most people only know about ChatGPT, but Claude has some features that you won't find in ChatGPT like it can handle massive context, refine drafts, and even simplify complex ideas for any audience. Here are 10
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Gemini 2.5 Deep Think Wins Gold at ICPC World Finals
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It was a busy week! Here’s a roundup of what we launched: — An advanced version of Gemini 2.5 Deep Think achieved gold-medal level performance at the 2025 ICPC World Finals — You can now share your @GeminiApp Gems with anyone — At this year’s #MadeonYouTube event, we
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Scaling Challenges: Finding Cost-Effective Solutions with Groq
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But scaling was brutal. Summarizing with GPT-3 was too expensive. Search APIs from Perplexity and Google drained cash fast. The dream was alive, but every query was burning through savings. That is when Paul found @GroqInc . -
Groq’s Compound System Makes Recall Knowledge Base Sustainable
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With Groq’s Compound system on GroqCloud, Recall finally became sustainable. Users could upload their entire knowledge base and get instant answers at a fraction of the cost with fast and affordable inference. It was no longer just another notes app. It became a knowledge -
Reverse-Engineering Thought Chains Improves LLM Reasoning Capabilities
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Open-ended reasoning is one of the hardest problems in reasoning LLMs rn. So in this paper, they aim to solve this by reverse-engineering plausible thought chains from good answers via a gradient-free search With DeepWriter-8B trained on this data outperforming top OS models!
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Essential LLM Concepts: Tokenization, Attention, and Sampling
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key topics to learn how llms work, all it takes is < 2 years if you have cs foundation > tokenization and embeddings
> positional embeddings (absolute, rope, alibi)
> self attention and multihead attention
> transformers
> qkv
> sampling params: temperature, top-k top-p
> kv