DeepSeek Search debuts on the Artificial Analysis Search Index at 69, 17th of 27 search products, at the lowest price of any paid Search API on the board @deepseek_ai launched its Search API on 17 October. We benchmarked it in our Stirrup agent harness, where GPT-5.6 Luna (medium) calls DeepSeek Search as its web_search tool to complete a combination of tasks from BrowseComp, DeepSearchQA and AA-Omniscience. At $0.75 per 1k searches, DeepSeek Search costs less per search than any other paid Search API we benchmark, below Octen, Parallel (turbo) and Parallel (fast) at $1. At about $0.032 per task, it is the 5th cheapest of 27 products, cheaper than 20 of the other 25 Search APIs (median $0.066) and level with Nimble (lite). TinyFish, Octen, Parallel (turbo) and Parallel (fast) cost less. Key benchmarking results for DeepSeek Search: ➤ Artificial Analysis Search Index: DeepSeek Search scores 69, a 36-point lift over the same model with no search (33). It sits between TinyFish at 71 and Linkup (standard) at 68 ➤ AA-Omniscience is DeepSeek Search's strongest benchmark: it scores 70% accuracy on our proprietary factual answer benchmark. This ranks 10th of 27, 3 points behind the joint leaders, Exa (auto, dynamic highlights) and Firecrawl (73%). BrowseComp, which needs multi-hop reasoning across several searches, is its weakest benchmark: at 63% it ranks 25th of 27, well behind the Perplexity variants and Octen (85% to 87%) ➤ Large search results: each search returns about 7k tokens, near the top of the board's range. Each result carries about 1.8k characters of passages from the page. This raises model cost: at about $0.023 per task, DeepSeek's model cost is the 2nd highest on the board, behind Linkup (flash, alpha) at $0.039 ➤ 128-character query limit: DeepSeek rejects queries longer than 128 characters. 6% of the agent's searches hit this limit, and for 87% of these, the model's first shorter rewrite worked Key details: ➤ Setup: GPT-5.6 Luna (medium) in Stirrup, DeepSeek Search API with need_content=false (page passages, no full page content) and 10 results per search ➤ Pricing: $0.75 per 1k successful searches. DeepSeek does not bill empty results ➤ Rate limit: 5 searches per second per account

SITUATION DETECTED: DeepSeek raised $15 billion in one of China’s largest funding rounds ever. Tencent was a major investor, per Bloomberg.

I asked Gemini 4 Argon to build the Shore Temple in Blender. The temple is approximately 1,300 years old, and the entire project took close to 16 hours. Even this video, including the music, was created by Gemini 4 Argon.

I've been using Claude Duet the last couple hours and I'll say this: It's EXCELLENT The multi tasking is probably the best in the space You get one simple thread you can talk to, and as you give it commands and prompts, it automatically spins up tasks on a list for you So instead of having to manage a ton of side chats that could get long or confusing, you have 1 chat, but it makes 'task' threads automatically that you can watch and monitor This allows you to just keep brain dumping ideas and tasks into the one thread, and not have to worry about the agent getting confused. The agent just will manage all the tasks for you Very similar to Claude Code's new 'projects' feature which was probably a beta test for this The coding was great. Built me a bunch of PRs quickly I was able to review. Proactivity was fantastic too. Came up with a bunch of tasks on its own and just asked me for the go ahead As expected it's also fantastic to talk to. Claude has long been the best model to converse with (outside Opus 5) and the carries over to Claude Duet Really pleased with the product, even in research preview. Very excited to see where it goes from here Definitely sign up for the wait list

Three teams in one month have pushed LLM decode forward with megakernels: Inferact on Google TPUs, AMD with TileRT and FlyDSL, and now NVIDIA on GB300, now live on InferenceX. We're excited to see these gains and dig into the engineering behind faster inference. Megakernels combine work that normally runs in separate programs. Here's why that matters and how each team's approach works. (1/8)🧵

SPACEXSI 🔥: Grok Bot now supports live artifacts where it can build reports, memos, and dashboards. Users can ask Grok Bot to edit these pages or keep them updated over time.

OpenAI says GPT‑5.6 Sol helped researchers uncover a critical PHP flaw before attackers did. Finding it was only the beginning: getting fixes ready took two months of coordination across maintainers, security companies and governments.

OpenAI just announced: GPT-6 Astra GPT-6.1 Sol GPT-6 Luna and Codex are coming natively to Google Cloud Vertex AI and Google Antigravity.

Bring your next video idea to life with Kling 4.0, now available on fal. #Kling4 #KlingAI

Researchers at @wiz_io put Gemini 4 Argon to the test against complex cyber threats. In real-world testing, it found more than two times more vulnerabilities than baseline models — catching a critical risk that previous frontier models missed. See how they did it ↓

Hackers reportedly used Claude and Grok to automate attacks targeting over 400 banks and other financial targets in Latin America. Via the information In one of the first documented cases of its kind, AI agents appear to have stolen data and accessed bank accounts with little human input. This makes attacks much easier to scale, potentially overwhelming defenders. I guess this is just the beginning

it's day 17 of tibo 28-day challenge and so far today openai has announced two updates first is partnership with google. openai models and codex are coming to google cloud, big news if you're google user second is chatgpt ads, team is expanding ads to 26 more countries, so more users will now see ads while chatting with gpt but don't worry ads will only show on free and go plans. plus, pro and enterprise stay ad-free so do these count as today big improvement or are we getting reset?

Mistral ❤️ NVIDIA Mistral AI partners with NVIDIA to “develop a new generation of AI-native engineering workflows powered by NVIDIA accelerated computing.” Additionally, Mistral's models will be integrated with NVIDIA Omniverse libraries for GPU-accelerated 3D scene generation.

Gemini 4 Carbon just entered partner Early Access Program and LMArena testing 👀 What leaks & early tests show so far: 1. Tested internally on Google's "Jetski" coding platform ("feels like Opus 5.5") 2. Noticeably better at 3D and way less lazy than Argon

astra went from "greatest model ever made" to "biggest disappointment of the year" in 6 weeks. I love AI twitter.

NVIDIA GTC Berlin Keynote is about to start soon! GPUs, Nemotron, Robotics and loads of other updates. Gonna do some live text reporting here. Watching 🍿

ICYMI 👀: ElevenLabs released Eleven Realtime Max and Mini speech-to-speech models. > Eleven Realtime v1 Max scores 98.8% on Big Bench Audio and starts speaking in 0.57s. > Eleven Realtime v1 mini is optimized for natural conversations at low cost. Both models are available on ElevenAgents platform and APIs.

Now *thats* some big upgrade: Tibo says logged-in Codex and Work users now get *permanent prompt caching.* That’s a big upgrade for long coding sessions. You can leave a large project conversation, come back hours or days later, and reuse the cached context without losing the benefit simply because you took a break.

Inception has released Mercury 3, a diffusion language model. Instead of writing one token at a time, it refines many tokens in parallel. Inception says it matches or beats GPT-6 Luna and Claude Haiku 5.5 on its benchmarks while running at 1,068 tokens per second on NVIDIA GPUs. It is more than 40 times larger than Mercury 1 and has a 1M-token context window, up from 260K in Mercury 2.5. Launch pricing is $0.10 per million input tokens and $0.35 per million output, half the list price. It is available on Inception's API, OpenRouter, Baseten and Vercel's AI Gateway. Mercury 2 and 2.5 are closed to new users, and existing users keep access until 15 November. The benchmarks are Inception's own and have not yet been tested independently. If they hold up, diffusion's speed advantage survives at a much larger scale, which matters most for voice assistants and agents that make many short calls while a person waits. inceptionlabs.ai/blog/introd…

Google just opened Gemini 4 Argon to Pro and Ultra subscribers in the Gemini app, and to developers via the paid API. Introductory price: $2 / $10 per million tokens until Nov 30.