Cassidy: Google just cut agent token costs by up to 65% — and the buyers of AI compute are fronting the cash for the buildout.
Cassidy: Same economy, both sides moving at once.
Cassidy: If you're just joining: IREN's AI-cloud expansion is one of the cleanest signals we've got of GPU capacity turning into contracted revenue.
Cassidy: The company says it signed 2.8 billion dollars in multi-year AI cloud contracts
Cassidy: raised its 2026 AI cloud ARR target above 4 billion
Cassidy: and laid out capacity growth from roughly 3 megawatts of self-built AI cloud to 480 megawatts scheduled for 2026 — with 1.2 gigawatts
Cassidy: targeted for 2027.
Bill: This is AI Daily Briefing — and today, one number finally landed where I've been pointing all week.
Bill: Let's start with Gemini 3.6 Flash.
Bill: Sixty-five percent off token cost on long-horizon engineering tasks.
Bill: That's a per-task price change on the exact workload agents chew through, not just another leaderboard headline.
Bill: IREN AI cloud expansion isn't over.
Bill: Follow us wherever you're listening, and the next chapter comes to you.
Cassidy: VentureBeat, with Carl Franzen:
Quote: Google DeepMind today released three new proprietary AI models it says are among its most token-efficient yet: Gemini 3.6 Flash
Quote: Gemini 3.5 Flash-Lite
Quote: and Gemini 3.5 Flash Cyber.
Quote: The models aim to make AI agents faster, smarter, and cheaper at scale.
Bill: Okay, the number I actually care about: Gemini 3.6 Flash, $1.50 per million input tokens, $7.50 output.
Bill: Flash-Lite drops to thirty cents in, two-fifty out.
Bill: That's the delta that changes build-versus-buy math for anyone running agents at volume.
Cassidy: And notice what VentureBeat's piece does not have attached: a technical report.
Cassidy: Sixty-five percent cost cut on long-horizon engineering tasks, quoted straight from the blog post.
Cassidy: Until someone runs it, that's still a vendor claim.
Bill: Right, and I'm not spiking the ball on it.
Bill: The 65% is a headline figure on their benchmark, with their task definition.
Bill: What I want is that curve on my workload — the ten-hour agent run where costs compound.
Cassidy: And there's still a 3.5 Pro coming, so the whole cost-performance ladder is moving under our feet.
Cassidy: You can't price a build decision against a lineup that isn't done shipping.
Bill: That's the trap, though.
Bill: Somebody's gonna sign a two-year inference commitment this week on a number from a model that'll be superseded by August.
Cassidy: Here's Shane Snider at Data Center Knowledge:
Quote: The company said recent contracts include customer prepayments covering roughly 45% of the GPU capital expenditures associated with those
Quote: deployments reducing IREN's net funding requirements.
Quote: An IREN spokesperson told Data Center Knowledge that such prepayments are “an increasingly common feature of AI cloud contracts,” suggesting
Quote: that customers are committing capital earlier to secure access to scarce AI compute.
Cassidy: So the IREN number came in: $2.8 billion in new multiyear contracts
Cassidy: and the year-end AI cloud ARR target moved from $3.7 billion to more than $4 billion.
Cassidy: This is the follow-on to the demand question we've been chewing on all week.
Bill: And the detail that actually matters is buried three grafs down: customers prepaying about 45% of the GPU capex up front.
Bill: The AI labs are co-investing to lock in capacity.
Cassidy: Right, that's the financing model Data Center Knowledge is treating as the template.
Cassidy: The tenant fronts nearly half the build, so IREN raises less on its own balance sheet.
Cassidy: Pay the capex early, get the compute.
Bill: Which changes the whole speculative-capex story.
Bill: IREN isn't building on a hope and a lease — they've got signed contracts and prepayments before the racks go in.
Bill: Different risk profile from the pre-revenue infra rounds I keep side-eyeing.
Cassidy: From SynBioBeta:
Quote: Chai Discovery a company focused on engineering AI models for the discovery of new molecules
Quote: has announced a $400M Series C funding round aimed at accelerating its advancements in the field.
Quote: This funding round which values the company at $3.8 billion
Quote: was led by Index Ventures
Quote: with participation from Kleiner Perkins
Quote: Sequoia Capital Dimension
Quote: and several existing investors.
Bill: Chai Discovery: $400 million Series C, $3.8 billion valuation, Index leading.
Bill: And here's what I actually want to know: what's that $400 million priced on?
Bill: Because a drug-discovery model doesn't bill per token like an enterprise agent.
Bill: The economics are completely different — you're betting on discovery outcomes
Bill: on a molecule that clears pre-clinical
Bill: not on inference run rate.
Cassidy: And look at that cap table: Sequoia, Kleiner, Bain, Baillie Gifford, and OpenAI's still in from earlier rounds.
Cassidy: The customers are Eli Lilly and Pfizer.
Cassidy: That's a very specific set of hands on the fine-tuning.
Bill: Second one of these in two days, too.
Bill: Same question I had on the materials-discovery raise: science-compute funding keeps getting valued like SaaS
Bill: and it just isn't the same bet.
Cassidy: Nina Achadjian's quote is pure founder-praise boilerplate — technical brilliance, commercial clarity.
Cassidy: What I wanted from the release was who owns the model weights when Pfizer's data goes in and a candidate comes out.
Cassidy: Cisco Blogs, with Amin Karbasi:
Quote: Today Cisco is introducing Antares
Quote: a family of security small language models (SLMs) purpose-built for one of the hardest
Quote: most time-consuming and expensive problems in security: pinpointing where known vulnerabilities exist within a codebase.
Quote: We are releasing two of these models—Antares-350M and Antares-1B—as open-weight models now available to the broader community on Hugging
Quote: Face.
Cassidy: Cisco dropped Antares today — two open-weight security models
Cassidy: 350M and 1B both on Hugging Face
Cassidy: with a named team and a technical write-up attached.
Cassidy: After the week we've had, an actual model release with receipts feels almost quaint.
Bill: And the task is narrow on purpose: pinpoint where a known vulnerability actually lives in a codebase.
Bill: That's the expensive, tedious part Cisco says nobody wants to do by hand.
Cassidy: What I like: they say these beat bigger closed and open models on that one task at a fraction of the cost
Cassidy: and they're small enough to run locally.
Cassidy: So you're not shipping your source code to somebody's cloud to find your own bugs.
Bill: That local part is the tell.
Bill: A 1B model on your own hardware
Bill: scoped to one job — that's a different agent-security bet from the off-script-reasoning pitches we heard yesterday.
Bill: This one's small enough that you can actually reason about its failure modes.
Cassidy: Now compare that with the demo drops this week, where the technical report is nowhere to be found.
Cassidy: Cisco gave us weights, a benchmark, named authors.
Cassidy: Hold that up as the bar.
Bill: I'll believe the benchmark when it survives a messy real repo, but being able to download it and check is the whole point.
Bill: It's cheaper to distrust, and I mean that as a compliment.
Cassidy: Inside Privacy is tracking this one, with Laura Kim, Alexandra Remick, and Munseong Park on the byline.
Bill: Connecticut signed a comprehensive AI bill back in May, and now they're extending it to subscription services.
Bill: So the same law that touches safety is reaching into cancel flows and auto-renewals.
Cassidy: Here's the confusion I keep hammering: one bill bundles model safety with consumer-protection subscription rules.
Cassidy: Those are two totally different regulatory problems under one signature.
Bill: And for anyone building on top of these APIs, that's the part that actually lands.
Bill: Your compliance surface just grew a subscription-disclosure obligation that has nothing to do with the model.
Cassidy: Covington's Inside Privacy has the breakdown — Kim, Remick, and Park walked through the May 27 signing.
Cassidy: If you ship in Connecticut, read that this week, not just the launch headlines.
Cassidy: If you follow AI Daily Briefing for the policy stakes
Cassidy: try Anthropic Pentagon Watch — a daily briefing on Anthropic's fight with the DoD over Claude
Cassidy: military AI use autonomous weapons
Cassidy: and procurement blacklisting.
Cassidy: Find it wherever you listen to podcasts.
Cassidy: What we're watching next: whether IREN hits its more-than-four-billion-dollar AI cloud ARR target by the end of 2026.
Cassidy: You'll find links to every story we covered today in the show notes.
Cassidy: If one caught your attention, that's where to dig in.
Cassidy: That's AI Daily Briefing for today.
Cassidy: This is a Lantern Podcast.