Chip startups keep drawing competitive rounds

Benchmark won a contested bid to lead a new round in Tendrils Compute, an early-stage chip startup based in Cambridge, UK, and led by Nils Cremer. People familiar with the deal say Tendrils is already discussing a quick follow-on that could value it above $1B Newcomer. The technical bet is unusual: general-purpose chips built on interaction nets, a graph-based computing model. The pitch is that CPU speed becomes a bottleneck as agents chain inference steps and tool calls Newcomer. Benchmark has done this before. It co-led Cerebras's 2016 Series A and earned about 20.5x when Cerebras went public Newcomer.

Volantis announced an $88M Series A for optical interconnects that target AI's memory bottleneck. Its claims include inference at up to 10,000 tokens/sec per user on models larger than 10T parameters. It says its next chip iteration has already taped out @semiDL. Newcomer lists other recent chip rounds:

• Etched: $700M at a $21B valuation
• Fractile: in talks at $6.5B after an Anthropic supply deal
• OLIX: $312M at $3.3B
• Euclyd and Delos Data: nine-figure rounds Newcomer

There is a counterweight. Cerebras traded as high as $386 after listing but now sits close to its $185 IPO price Newcomer.

Cheap "decision models" are becoming their own category

Perplexity is open-sourcing pplx-decider-27b, a multimodal model that outputs a probability distribution over a fixed set of answers instead of free text. It is served through a Decisions API at $0.04 per million input tokens with free output, and Perplexity says the price will drop further @AravSrinivas +1. Cloudflare open-sourced its first homegrown decision models, clef and clef-flash, on Workers AI the same day @ritakozlov. Harrison Chase described the use case: cheap typed answers for small calls inside a harness, such as routing, approvals and judging, with a big model handling everything else @hwchase17.

Jev from TypeSafe AI started this category. On 20VC x SaaStr, the hosts said TypeSafe raised a $40M seed at $200M and is now in talks to raise more than $1B at a valuation above $10B. Jason Lemkin cited Jev at 17% of OpenRouter traffic SaaStr. With two open-weight entrants priced about the same, the main question for anyone underwriting TypeSafe at that valuation is how defensible it is.

LangChain published data supporting routing. In a 973-thread A/B test, its Open SWE harness either routed each task to the cheapest adequate model tier or always used GPT-6 Astra. Merged-PR rates were 29.2% routed and 27.3% control, a difference that was not statistically significant (p=0.49). Median cost per thread fell 64%, from $2.61 to $0.94 @sydneyrunkle. A fast-model-only arm was stopped within a day because output quality was too low @sydneyrunkle.

The 20VC x SaaStr panel on venture now

Benchmark's Jack Altman joined the panel because Benchmark co-led Instinct's $1B round at $10B. That round came 33 days after Instinct was raising at $2.5B. The founder says Instinct is approaching $1B in annual transactions, more than half of them travel SaaStr. Main threads:

• Neolab exits. AMD's $8.2B all-stock purchase of World Labs, about 2.5 years after founding, was described as the first big neolab exit. One partner's tally counts 102 neolabs that have raised more than $70B. Altman's answer was that about 10 companies can now do $10B acquisitions, which he called faster than an IPO SaaStr.
• Seed sizing. Altman called $3–6M checks for 8–15% ownership "broken in many lanes." His reasoning: labs need $200M or more, and well-networked founders skip straight to $50M rounds. Lemkin's view is that $2–3M is still the natural seed size when investors aren't competing to fund you SaaStr.
• Inference and open weights. Modal tripled its valuation to $15B and Baseten is in talks at $26B. Altman called inference an index bet on everything outside the labs SaaStr. Lemkin thinks open-weight share has peaked. He cites closed-model price cuts and says he couldn't find an enterprise at Dreamforce willing to run mostly China-origin open weights. Altman expects more enterprise post-training on open weights, but thinks compute ownership decides the outcome SaaStr.
• IPOs. Oura pulled a $15.62B IPO two days before pricing despite reports the book was oversubscribed. One panelist pointed to Forerunner's plan to sell its entire stake, which makes sellers very price-sensitive. Altman noted no AI-native application company has gone public yet, and expects several in 2027 if markets hold SaaStr.

SaaStr's reading of a16z's market deck adds data on how spread out outcomes have become:

• Under-one-year-old B2B companies are growing more than 500% year over year. Mature B2B companies are at about 24% SaaStr.
• 55% of US unicorns have less than two years of runway SaaStr.
• For the 2024 vintage, top-decile VC net IRR is 40.5% against a -3.3% median. Median DPI is 0.00x for every vintage since 2021 SaaStr.

Early-stage rounds and teams

• doxxnet (Barrett Lyon, co-founder of Prolexic) raised $38M led by a16z. The product is private networks for people and their AI agents with no server in the middle, and the company says it has blocked 38M+ threats since December @BarrettLyon +1. a16z's thesis is that agents widen the personal attack surface @a16z.
• Halluminate builds reinforcement-learning environments for knowledge work beyond coding, starting with finance. With fewer than 10 people, it works with four of the top five closed US labs and recently raised a $30M Series A. Its founders argue verification matters more than task volume @ycombinator.
• Harmonic's Hot 25 ranks Resolve AI first for the third time. The Latent Co is the top newcomer at #2, with Prime Intellect, Strala AI and Trajectory Labs also new to the list @HarryStebbings.
• YC promoted founders Vivian Shen (Juni, Acely) and Raphael Schaad (Cron) to General Partner @ycombinator. Garry Tan says the partnership now has 19 members, the largest in its history @garrytan.
• Imbue Studio went to waitlist. It is pitched as a personal computer you shape by describing what you want, open source under FSL, runnable locally, and able to switch between AI providers @kanjun +1.
• AMI Labs. Yann LeCun says it is still in research with no short-term product plan, has 50–60 staff across Paris, New York, Montréal and Singapore, plans more funding rounds to pay for compute, and does not intend to be acquired La Tribune Événements.

Models and research

Google DeepMind's Gemini 4 Argon is available first only to government users and trusted cyber defenders Latent.Space. Artificial Analysis scores it level with GPT-6 Astra, at $1.99 per task versus $3.26. The savings come from introductory pricing, not efficiency: Argon uses 62K output tokens per task against Astra's 27K Latent.Space. Vals lists 262K maximum output tokens against Google's 1M claim Latent.Space.

LlamaIndex says its Extract v2.5 document-extraction agents beat Opus 5.5 and GPT-6 Sol while costing 30% to 4x less @jerryjliu0. arXiv now limits each submitter to two submissions per calendar month r/MachineLearning.