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  4. Exa 3.0 Search API Tops Perplexity, Brave and Parallel on 8 Benchmarks
Models & Releases30Funding & Deals18Benchmarks14Agents & Products50Hardware & Compute15Policy & Drama31Robotics12
Benchmarks

Exa 3.0 Search API Tops Perplexity, Brave and Parallel on 8 Benchmarks

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 serve

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A company has released an upgraded web search API designed for AI agents, featuring a larger embedding model and a new cheaper search option. The company claims its search tool ranks first on eight benchmarks when compared to three competitors, though these benchmarks were run by the company itself rather than by independent evaluators. The upgrade includes expanded data coverage such as e-commerce listings, local businesses, news, and weather information, along with a feature called Dynamic Highlights that reduces token usage by 95 percent compared to full page text at no additional cost. The practical benefit for developers is lower costs, with the new lite search type priced at four dollars per one thousand requests.

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Deepseek V4.1 Flash 1017 beats larger rivals in agentic tasks while once again massively cutting per-task costs

Deepseek has released V4.1-Flash-1017 as an open-weight model that posts better benchmarks, finishes tasks faster, and produces shorter outputs than its predecessor. The company is also opening up its internal search engine through new Search and Fetch APIs at $0.75 per 1,000 calls. API users in tools like Claude Code and Codex get free access for now. The article Deepseek V4.1 Flash 1017 beats larger rivals in agentic tasks while once again massively cutting per-task costs appeared fir

Also reported by SiliconANGLE

BenchmarksOpen story →

Four Gemini 4 Argon agents beat Minecraft without any human help

Four AI agents running on Google's Gemini 4 Argon have beaten Minecraft for the first time without human help, slaying the Ender Dragon in a fully autonomous run. With no predefined roles or strategies, they coordinated on their own, wrote 2,783 programs, exchanged 229 chat messages, and died 605 times. The session cost $1,620. The article Four Gemini 4 Argon agents beat Minecraft without any human help appeared first on The Decoder.

BenchmarksOpen story →

ALTK-Evolve: How learned memory tops the τ²-bench leaderboard on customer service tasks without a frontier model

A system using adaptive memory mechanisms outperformed larger proprietary models on customer service benchmarks, suggesting scale isn't the only path to performance.

BenchmarksOpen story →

Anthropics' Claude cracks a 25-year-old NSA cryptography mystery in under 30 minutes

Anthropic's AI model Claude has solved a 25-year-old cryptography puzzle. The mysterious seeds behind NIST's standard curves for digital signatures were provided by the NSA without explanation, raising long-standing suspicion about built-in backdoors. Claude figured out in under 30 minutes that the seeds came from "lrand48," a simple C random number generator, making deliberate backdoors far less likely. The article Anthropics' Claude cracks a 25-year-old NSA cryptography mystery i

BenchmarksOpen story →

Elorian’s first AI model wants to reason with images, not just about them

According to Elorian's evaluations, Glimpse outperforms even GPT-6 Astra on scientific chart reasoning and short-form video captioning, with competitive results on other visual reasoning tasks.

BenchmarksOpen story →

Google's Gemini 4 Argon is closer to the AI frontier than any Google model in months

Google Deepmind's Gemini 4 Argon scored 97.5 percent on the ARC-AGI-3 benchmark, making Google the second lab after OpenAI to cross the 95 percent mark. But the results swing wildly depending on the test setup: in the standard harness, the score drops to just 49.8 percent. Argon also trails rivals in math and software engineering. The article Google's Gemini 4 Argon is closer to the AI frontier than any Google model in months appeared first on The Decoder.