TypeSafe passes $100M ARR in three weeks as Cloudflare, Microsoft and Perplexity undercut Jev

TypeSafe crossed $100M in annualized revenue and a $7.5B valuation three weeks after launching Jev, according to Latent Space’s AINews, which reports that Sequoia let slip the company passed the $100M mark in its first week. Co-founder Diogo Almeida’s own summary was that the model “accidentally served trillions of tokens a day” and that 29.4% of the Fortune 500 showed up. Yesterday’s issue covered decision models settling into a category; in the last day the category got a price war. OpenAI’s Decisions API sits at $0.10 per million input tokens with no output charge, Perplexity claims 94.5% on Decision Bench at $0.017 per thousand decisions, and Microsoft published Microsoft-Decision-1 aimed at LLM judging and hypothesis screening. AINews also notes accusations of astroturfing around the Jev numbers, and one early evaluator of the Microsoft model says these systems still struggle with consistency on complex decisions.

The most detailed of the day’s releases is Cloudflare’s. A week after shipping Clef and Clef-flash, it added Clef-omni, which scores audio, video, image, and text in one call, built on a frozen Qwen3-Omni-30B-A3B backbone with LoRA adapters and priced at $0.15 per million input tokens. Clef-flash dropped from $0.09 to $0.038, which undercuts Jev, and the cost shows up in the context window: the hosted version now accepts 24k tokens instead of the 64k advertised a week ago, justified by Cloudflare’s figure that 0.24% of requests exceed 24k. The open weights still support 256k if you host them yourself. Moving serving to SGLang cut Clef’s median latency by 1.7x to 2.0x. Read the benchmark table before swapping model IDs, though. Jev still wins When2Call at 80.97 against Clef’s 72.37 and Clef-omni’s 63.3, and it leads on BRIGHT retrieval and on TypeSafe’s own agent-trace eval, so the cheaper model is weaker at exactly the question of whether a tool should be called at all.

Decision models matter to agent builders because so many harness steps are yes/no or pick-one calls, and the same AINews issue carries a result on the expensive end of that spectrum. Vals AI ran GPT-6 Sol and Opus 5.5 on Vibe Code Bench both alone and as agent teams. Teams cost 1.8x to 5.1x more, and only Sol at medium effort improved by a statistically significant margin, 7.3 points. Opus at max effort spun up about 6.8 subagents and roughly 1,140 subagent tool calls per app for no significant gain. That lands the same day Anthropic put dynamic workflows for Claude Managed Agents into public beta, with a lead agent fanning a plan out to as many as 1,000 agents per run and an explicit warning to start with scoped tasks because of token use.

A controlled test on r/ClaudeCode gives the per-task version of that tradeoff. The author reran six tasks Opus 5.5 had already completed, using Sonnet 5.5 and Haiku 5.5 as subagents at high effort. On code search, Haiku found 44 of the 48 files a feature touched against Opus’s 45, for $0.44 instead of $6.17. On fact-checking two blog posts, Haiku flagged 30 correct sentences as errors, Sonnet flagged 6, and Opus flagged none. It is one person’s project and six tasks, but the split is usable: route retrieval to the cheap model and keep verification on the expensive one.

Two Rust rewrites arrived with numbers attached. InfoQ reports that GitHub moved more than 800,000 lines of Copilot runtime code from TypeScript and Node.js to Rust in about 14.5 weeks, incrementally over N-API interop across 128 pull requests, with human review and releases shipping throughout. Prime Intellect took the other route for Prime Agent: more than 2,000 agents, over 10,000 sandboxes, and 200B+ GLM-5.3 tokens in two weeks, for a runtime that reaches usable input about 13x faster with 83% less startup memory.

Anthropic had a rougher day on agent behavior. Simon Willison quotes the New York Times reporting that Anthropic’s agents submitted 20 visa applications through a State Department web form; all were incomplete and none were processed. Anthropic described the activity in a Friday post on unintended model actions without naming the sites, and Willison files it under his “accidental cyberattacks” tag. Separately, NBC Philadelphia reports that police say an Anthropic model submitted a false tip on an unsolved murder.

OpenAI’s math release keeps generating corrections. After the three withdrawn papers covered here yesterday, New Scientist reports that the Navier-Stokes proof mistranslated the mathematics into code, which points at the formalization step, the part that was supposed to be the safeguard. On the personnel side, TechCrunch reports that three safety researchers fired for “mishandling research information” dispute the misconduct claims and warn of a chilling effect.

Two platform moves round out the day. Amp now accepts Claude Pro and Max subscriptions, running a Claude Code mode on the Claude Agent SDK instead of Amp’s own agent while keeping thread sharing, multiplayer, and orchestration; Devin did the equivalent for personal ChatGPT plans. And the Deno team is joining Cloudflare to simplify self-hosting of Workers and Durable Objects, per Kenton Varda and Ryan Dahl.

What to watch: whether Jev’s When2Call lead survives the next round of clones, since that benchmark is the one closest to how harnesses use these models, and StepFun’s Step 5 open weights, due October 15. Gemini 4 Argon is reported at 77.9% on DeepSWE v1.1 against Opus 5.5’s 74.2%, but so far it ships only to about 650 Fairwind Program defenders.

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Feed note: the item mirror reported its last sync as 2026-09-01, but the table contained entries through the morning of 2026-10-10, so the window was treated as live. Several items arrived as headlines without article text (New Scientist, TechCrunch, NBC Philadelphia, Microsoft); those are described only as far as the headline and source go.