World Wire

Exa has released Exa 3.0 , an upgrade to its web search API for AI agents. The Exa 3.0 search API ships a larger embedding model and a cheaper search type, Exa Lite. Dynamic Highlights is now generally available. Exa claims that it leads Perplexity, Brave and Parallel on 8 benchmarks. Those benchmarks were run by Exa, so you can treat them as self-reported. For developers, the practical change is cost: Lite costs $4 per 1,000 requests . TL;DR Size: Exa tracks over 2 trillion URLs and serves 100 billion pages. Embedding model size: Not disclosed. Runs on: Hosted API only. Exa lists configurable search latency of 450ms to 1s . No self-hosted option. Performance: Exa 3.0 Auto ranks first on all 8 Exa-run benchmarks against Perplexity, Brave and Parallel. Best: 91.8% on BrowseComp, plus the widest lead on ATLAS (42.0% vs 37.2% for Perplexity). Worst: 42.0% on ATLAS is its lowest percentage score. Its BrowseComp lead over Perplexity is only 0.3 points. W...

Cloudflare has released a preview of Clairic , a new System One extraction model on Workers AI. The Cloudflare Clairic extraction model reads text or images and returns typed values, not generated text. It targets a job developers usually give to LLMs: pulling totals, dates and IDs into JSON. Clairic answers every requested field in 1 forward pass, with no reasoning and no output tokens. TL;DR Size: Parameter count not disclosed. 65,536-token context window , up to 4 images per request. Runs on: Cloudflare-hosted GPUs via Workers AI ( @cf/cloudflare/clairic ). No local option until weights ship. Performance: Sub-second extraction in Cloudflare’s tests. No standard accuracy benchmark is published yet. Best: Extraction step took 0.46 s vs 16.1 s for GLM-5.3 in Cloudflare’s claims pipeline. Worst: 4 of 21 TSA next-day forecasts fell outside its 80% interval. Multi-step arithmetic is unreliable. What is Clairic? Clairic is a Cloudflare mo...

Inception has released Mercury 3 , the newest version of its diffusion language model. Mercury 3 is a diffusion LLM from Inception that writes answers in parallel, not token by token. Inception reports 1,068 tokens per second on NVIDIA GPUs and a 1M-token context window. On Inception’s own benchmark table, it leads GPT-6 Luna and Claude Haiku 5.5 on 8 of 12 tests. For developers building agents, voice bots and search tools, this is a speed-first model with competitive scores. TL;DR Size: Parameters not disclosed. Inception says it is more than 40x larger than Mercury 1. Context is 1M tokens. Runs on: Inception-served NVIDIA GPUs (exact GPU not disclosed). API only, no open weights or quantized builds. Performance: Leads 8 of 12 benchmarks vs GPT-6 Luna and Haiku 5.5 (self-reported, medium settings). Best: SWE-Bench Atlas 51.08, about 18 points ahead of both rivals. Worst: DeepSWE v1 46.31, 5.31 points behind Haiku 5.5 (51.62). What is Mercury 3?...