Mercury 2.5 is the most capable diffusion LLM on the market. It runs at 1,107 tokens/sec and offers a 40% increase in intelligence over Mercury 2, comparable to cost-optimized frontier models.
Diffusion at Scale: Introducing Mercury 3 – Inception
Mercury 3 is the most capable diffusion LLM released to date. It outperforms GPT-6 Luna and Claude Haiku 5.5 while running 4–8x faster at 1,000+ tokens per second.
Research – Inception
We are leveraging diffusion technology to develop a new generation of LLMs. Our dLLMs are much faster and more efficient than traditional autoregressive LLMs.
State of AI 2025: 100T Token LLM Usage Study | OpenRouter
Read OpenRouter's 2025 State of AI report — an empirical 100 trillion token study of real LLM usage, model trends, and developer insights.
The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities (Version 1.0)
LLM Leaderboard - Comparison of over 100 AI models from OpenAI, Google, DeepSeek & others
Comparison and ranking the performance of over 100 AI models (LLMs) across key metrics including intelligence, price, performance and speed (output speed - tokens per second & latency - TTFT), context window & others.
LLaDA - Large Language Diffusion Models
LLaDA is a diffusion model with an unprecedented 8B scale, rivaling LLaMA3 8B in performance.
LLMs Can Now Write GPU Kernels That Beat torch.compile - Break AI Scaling Limits in 7 Days
We're now seeing multi-agent systems that take your PyTorch code and produce CUDA or Triton kernels with 2x to 14x speedups over torch.compile(mode='max-autotune-no-cudagraphs'). Not on toy benchmarks. On real models like Llama-3.1-8B, Whisper, and Stable Diffusion. Learn proven techniques to shift the scaling law intercept and achieve 10-50% performance gains.
LLM Leaderboard 2026 — Compare Top AI Models
Compare the latest LLM benchmarks for GPT, Claude, Gemini and more. Updated rankings across reasoning, coding, math, and multilingual tasks with pricing and speed data.
576 - Using LLMs at Oxide | RFD | Oxide
Large language models (LLMs) are an indisputable breakthrough of the last five years, potentially profoundly changing the way that we work. As with any extraordinarily powerful tool, LLM use has both promise and peril — and that they are so general-purpose leaves real questions about how and when they should be used. The landscape is shifting so rapidly that static prescription is unlikely — but that LLMs are evolving so quickly also gives urgency to the question: how should LLMs be used at Oxide?
576 - Using LLMs at Oxide | RFD | Oxide
Large language models (LLMs) are an indisputable breakthrough of the last five years, potentially profoundly changing the way that we work. As with any extraordinarily powerful tool, LLM use has both promise and peril — and that they are so general-purpose leaves real questions about how and when they should be used. The landscape is shifting so rapidly that static prescription is unlikely — but that LLMs are evolving so quickly also gives urgency to the question: how should LLMs be used at Oxide?
Rohan Paul on Twitter / X
The paper shows real LLM query energy is lower than popular claims, and maps concrete ways to shrink it.A normal frontier model query uses about 0.34 Wh in real deployments.Many public numbers are 4x to 20x too high because of tiny tests and unclear scopes.They estimate… pic.twitter.com/FiGFt0bTiH— Rohan Paul (@rohanpaul_ai) September 26, 2025
DiffusionGemma as Jev: Open-Source vLLM Patch (2026) | explainx.ai Blog
A vLLM contributor built an open-source Jev clone using DiffusionGemma — roughly matching TypeSafe's proprietary model on accuracy.
Alex Cheema on Twitter / X
.@karpathy shouted out my work on @exolabs at @ycombinator AI SUS!“we use LLMs similarly to mainframes in the ‘70s - compute is timeshared by having a slice in the batch dimension. models will compress over time, and with this we’ll be able to run more on-device” pic.twitter.com/UKSrquQGAL— Alex Cheema (@alexocheema) June 18, 2025
distil labs – Cut LLM Costs by 80% with Custom SLMs
Your LLM costs are eating your product margins. distil labs trains a specialized model layer on your workload and serves it behind one OpenAI-compatible endpoint.
What sort of maths are LLMs good at?
For the sake of anyone who might read this blog post in the distant future (a month from now, say), let me mention that I am writing it a few days after OpenAI announced that it had solved ten majo…
