#PicoPrism #Ethereum

In mid-October 2025, a new entrant called Brevis released its “Pico Prism” technology — and the ripple effects across the Ethereum ecosystem have been far from subtle. The announcement caught the attention of the Ethereum Foundation itself, with the official account tweeting:“This is a major step toward Ethereum’s future. ZK technologies like Pico Prism will enable Ethereum to scale to global demand while still remaining trustworthy and decentralized.”

Prominent figures in the ecosystem, including Vitalik Buterin and core-developer Justin Drake, likewise lauded the achievement.

But beyond the fanfare, what exactly is Pico Prism? Why is it being treated as a potential game-changer? And what are the caveats that merit a more measured view? This article unpacks the technology, its significance for Ethereum’s scalability roadmap, and the open questions that remain.

At its core, Pico Prism is a zero-knowledge proof (ZKP)-based system developed by Brevis, designed for “real-time proving” of Ethereum L1 blocks. According to Brevis:

• In benchmark testing of Ethereum blocks (rated at a 45 M gas limit), Pico Prism achieved 99.6% coverage of blocks proven in under 12 seconds.Specifically, 96.8% of blocks achieved under 10 seconds proving time — a key milestone tied to Ethereum’s roadmap.

• Average proving time reported was ~6.9 seconds (for 45 M gas blocks), compared with previous benchmarks (e.g., ~10.3 s) using older hardware/architectures.

• Cost and hardware improvements: while a prior system (Succinct SP1 Hypercube) needed ~160 RTX 4090 GPUs (~US$256 k hardware cost) per cluster, Pico Prism achieved similar or better throughput with just 64 RTX 5090 GPUs (~US$128 k hardware cost) — roughly a 50% cost reduction plus ~3.4× performance improvement when combining speed and cost.

In concrete terms: rather than every validator re-executing every transaction in a block (the current model for Ethereum L1), Pico Prism’s model is: one prover generates a ZK proof for the block, and the rest of the network merely verifies that proof — vastly reducing computation for the verifying nodes.

• Multi-machine, multi-GPU pipeline: the proving process has been broken into stages (emulation → recursive proving) and off-loads compute-intensive work to GPUs, leaving setup tasks on CPUs. This modular design enables near-linear scaling across multiple servers.

• Use of consumer-grade hardware (RTX 5090) rather than costly data-centre-only infrastructure, thereby lowering barriers for validator infrastructure and promoting decentralisation.

Ethereum block time currently sits around ~12 seconds. Real-time proving (RTP) means the proof for a given block is produced in less (or not much more) than that interval — ideally <10 sec — so that proof-based validation can keep up with block production speed. When validated quickly, validators no longer need to re-execute every transaction in the block; they just verify the proof. That has implications for throughput, node hardware requirements, decentralisation, and cost.

Ethereum has long straddled the “scalability vs. decentralisation vs. security” trilemma. Its current model (on L1) means every validator must re-run every transaction in every block. As usage grows, this becomes a bottleneck: large block sizes increase hardware demands, limit validator participation (centralisation risk), and keep gas costs high.

Pico Prism’s breakthrough is important for the following reasons:

If validators only need to verify a small ZK proof rather than re-execute entire blocks, their hardware requirements drop dramatically. Brevis argues that nodes could potentially run from much smaller hardware (even home-server or laptop class) rather than large rigs. A more decentralised validator set guards against centralised control and thus improves security/trust.

By shifting from re-execution to proof verification, block production can scale. Ethereum’s roadmap suggests aiming toward ~10,000 TPS (transactions per second) on L1 (post major upgrades like Fusaka/EIP-7825 etc). Pico Prism is cited as one of the technology enablers.

High gas fees on L1 are in part due to compute intensity and block size limits. If block validation becomes cheaper (via RTP), then higher throughput and lower fees become more feasible. Also the lowering of hardware cost for proving clusters (US$128k vs previous US$256k) makes broader infrastructure deployment economically viable.

Greater base-layer capacity and lower costs open the door for more complex dApps: DeFi, gaming, real-world assets, cross-chain protocols. It also makes L1 more competitive relative to L2s or alternative chains. Vitalik’s remark underlines this: RTP/ZK integration like Pico Prism are “a major step toward scaling while maintaining trust/decentralisation”.

The Ethereum Foundation’s July 2025 roadmap set explicit goals for real-time proving, ZK-EVM integration, and hardware/cost targets. Key targets included:

• ≥99 % block coverage under proving targets

• <10 sec proof time for “most” blocks

• Hardware cost for proving cluster <US$100 k

• Power consumption <10 kW (to make home validation feasible)

Pico Prism, while not yet hitting all “ideal” targets, has significantly narrowed the gap (96.8% <10 s, cost ~US$128k). It demonstrates progress from research toward production-grade infrastructure.

Justin Drake noted that upcoming upgrades (e.g., EIP-7825) will optimise L1 block structure to better support parallel proving/sub-blocks — making technologies like Pico Prism more effective.

While the numbers are compelling, a balanced analysis must consider caveats.

The benchmark results (e.g., 6.9 seconds average proof time for 45 M gas blocks) are promising. But they are measured in controlled testing conditions (“ama 1,000 blocks sampled” etc) rather than under full live network conditions where block conditions vary, forks occur, network latency matters, and adversarial conditions apply.

Even though Pico Prism lowered GPU count/cost, it still requires 64 high-end GPUs (RTX 5090) for the benchmark cluster. That means some infrastructure cost and sophistication remains; whether many independent actors will deploy such clusters remains to be seen. If only a few entities can run proving clusters, we could face centralisation of proving capacity (even if verification remains decentralised).

Transitioning many validators to “just verifying proofs” instead of full re-execution involves economic incentives, consensus protocol changes, software upgrades, and ecosystem alignment. If the incentives are misaligned (e.g., cheaper hardware but lower rewards) validators may delay adoption.

ZK proof systems introduce new cryptographic assumptions and complexity. While proving entire Ethereum blocks via ZK is technically viable, the security of the proving system, resilience against bugs, ensuring soundness/completeness, and decentralised upgrading are non-trivial. The network must ensure the prover(s) cannot cheat or collude.

Pico Prism is one piece. For Ethereum’s L1 to fully shift toward proof-based validation, other pieces must align: consensus layer changes, block size/gas re-thinking, client software, network upgrade coordination. Without holistic alignment, the benefit may be delayed.

• dApp builders can look forward to lower base-layer fees and higher throughput options.

• But they should also monitor how quickly real-time proving solutions like Pico Prism move from testing → production → full node support.

• Projects targeting L1 might see fewer scalability constraints, but still need to account for transition risk.

• Hardware requirements may drop in the medium term (less need for full re-execution rigs).

• Opportunity for “light-node” or home-validation becomes more realistic — which could broaden participation and decentralisation.

• Providers of proving clusters (e.g., Brevis-type infra) may become new infrastructure players; risk of concentration needs monitoring.

• The shift toward ZK-proof-based validation shifts the paradigm: trust moves from raw compute to cryptographic validity. Governance and audits must adapt.

• Upgrades like EIP-7825 and roadmap changes will need coordination across clients, protocols, and validators.

• The economic model of Ethereum (fees, gas, block size) may evolve — fees may drop, but block size/gas limit decisions become more critical.

Pico Prism is by no means a silver bullet — but it represents a meaningful advance in the push toward Ethereum’s next growth phase. Its achievement — near-10-second proof times, consumer-hardware clusters, cost reduction — crosses several “hard lines” in Ethereum’s scaling challenge.

For participants — developers, validators, and investors alike — the takeaway is cautious optimism. The foundation for transformative change is taking shape, but execution, ecosystem alignment and decentralisation still need to be proven in real-world conditions. Real-time proving is not just a technical feat — it’s a critical enabler for Ethereum’s next chapter.

Disclaimer: This article is for informational and educational purposes only. It does not constitute financial advice or a recommendation to invest. The technologies, timelines and performance metrics described are subject to change and depend on many variables.

#PicoPrism #Ethereum

In mid-October 2025, a new entrant called Brevis released its “Pico Prism” technology — and the ripple effects across the Ethereum ecosystem have been far from subtle. The announcement caught the attention of the Ethereum Foundation itself, with the official account tweeting:“This is a major step toward Ethereum’s future. ZK technologies like Pico Prism will enable Ethereum to scale to global demand while still remaining trustworthy and decentralized.”

Prominent figures in the ecosystem, including Vitalik Buterin and core-developer Justin Drake, likewise lauded the achievement.

But beyond the fanfare, what exactly is Pico Prism? Why is it being treated as a potential game-changer? And what are the caveats that merit a more measured view? This article unpacks the technology, its significance for Ethereum’s scalability roadmap, and the open questions that remain.

At its core, Pico Prism is a zero-knowledge proof (ZKP)-based system developed by Brevis, designed for “real-time proving” of Ethereum L1 blocks. According to Brevis:

• In benchmark testing of Ethereum blocks (rated at a 45 M gas limit), Pico Prism achieved 99.6% coverage of blocks proven in under 12 seconds.Specifically, 96.8% of blocks achieved under 10 seconds proving time — a key milestone tied to Ethereum’s roadmap.

• Average proving time reported was ~6.9 seconds (for 45 M gas blocks), compared with previous benchmarks (e.g., ~10.3 s) using older hardware/architectures.

• Cost and hardware improvements: while a prior system (Succinct SP1 Hypercube) needed ~160 RTX 4090 GPUs (~US$256 k hardware cost) per cluster, Pico Prism achieved similar or better throughput with just 64 RTX 5090 GPUs (~US$128 k hardware cost) — roughly a 50% cost reduction plus ~3.4× performance improvement when combining speed and cost.

In concrete terms: rather than every validator re-executing every transaction in a block (the current model for Ethereum L1), Pico Prism’s model is: one prover generates a ZK proof for the block, and the rest of the network merely verifies that proof — vastly reducing computation for the verifying nodes.

• Multi-machine, multi-GPU pipeline: the proving process has been broken into stages (emulation → recursive proving) and off-loads compute-intensive work to GPUs, leaving setup tasks on CPUs. This modular design enables near-linear scaling across multiple servers.

• Use of consumer-grade hardware (RTX 5090) rather than costly data-centre-only infrastructure, thereby lowering barriers for validator infrastructure and promoting decentralisation.

Ethereum block time currently sits around ~12 seconds. Real-time proving (RTP) means the proof for a given block is produced in less (or not much more) than that interval — ideally <10 sec — so that proof-based validation can keep up with block production speed. When validated quickly, validators no longer need to re-execute every transaction in the block; they just verify the proof. That has implications for throughput, node hardware requirements, decentralisation, and cost.

Ethereum has long straddled the “scalability vs. decentralisation vs. security” trilemma. Its current model (on L1) means every validator must re-run every transaction in every block. As usage grows, this becomes a bottleneck: large block sizes increase hardware demands, limit validator participation (centralisation risk), and keep gas costs high.

Pico Prism’s breakthrough is important for the following reasons:

If validators only need to verify a small ZK proof rather than re-execute entire blocks, their hardware requirements drop dramatically. Brevis argues that nodes could potentially run from much smaller hardware (even home-server or laptop class) rather than large rigs. A more decentralised validator set guards against centralised control and thus improves security/trust.

By shifting from re-execution to proof verification, block production can scale. Ethereum’s roadmap suggests aiming toward ~10,000 TPS (transactions per second) on L1 (post major upgrades like Fusaka/EIP-7825 etc). Pico Prism is cited as one of the technology enablers.

High gas fees on L1 are in part due to compute intensity and block size limits. If block validation becomes cheaper (via RTP), then higher throughput and lower fees become more feasible. Also the lowering of hardware cost for proving clusters (US$128k vs previous US$256k) makes broader infrastructure deployment economically viable.

Greater base-layer capacity and lower costs open the door for more complex dApps: DeFi, gaming, real-world assets, cross-chain protocols. It also makes L1 more competitive relative to L2s or alternative chains. Vitalik’s remark underlines this: RTP/ZK integration like Pico Prism are “a major step toward scaling while maintaining trust/decentralisation”.

The Ethereum Foundation’s July 2025 roadmap set explicit goals for real-time proving, ZK-EVM integration, and hardware/cost targets. Key targets included:

• ≥99 % block coverage under proving targets

• <10 sec proof time for “most” blocks

• Hardware cost for proving cluster <US$100 k

• Power consumption <10 kW (to make home validation feasible)

Pico Prism, while not yet hitting all “ideal” targets, has significantly narrowed the gap (96.8% <10 s, cost ~US$128k). It demonstrates progress from research toward production-grade infrastructure.

Justin Drake noted that upcoming upgrades (e.g., EIP-7825) will optimise L1 block structure to better support parallel proving/sub-blocks — making technologies like Pico Prism more effective.

While the numbers are compelling, a balanced analysis must consider caveats.

The benchmark results (e.g., 6.9 seconds average proof time for 45 M gas blocks) are promising. But they are measured in controlled testing conditions (“ama 1,000 blocks sampled” etc) rather than under full live network conditions where block conditions vary, forks occur, network latency matters, and adversarial conditions apply.

Even though Pico Prism lowered GPU count/cost, it still requires 64 high-end GPUs (RTX 5090) for the benchmark cluster. That means some infrastructure cost and sophistication remains; whether many independent actors will deploy such clusters remains to be seen. If only a few entities can run proving clusters, we could face centralisation of proving capacity (even if verification remains decentralised).

Transitioning many validators to “just verifying proofs” instead of full re-execution involves economic incentives, consensus protocol changes, software upgrades, and ecosystem alignment. If the incentives are misaligned (e.g., cheaper hardware but lower rewards) validators may delay adoption.

ZK proof systems introduce new cryptographic assumptions and complexity. While proving entire Ethereum blocks via ZK is technically viable, the security of the proving system, resilience against bugs, ensuring soundness/completeness, and decentralised upgrading are non-trivial. The network must ensure the prover(s) cannot cheat or collude.

Pico Prism is one piece. For Ethereum’s L1 to fully shift toward proof-based validation, other pieces must align: consensus layer changes, block size/gas re-thinking, client software, network upgrade coordination. Without holistic alignment, the benefit may be delayed.

• dApp builders can look forward to lower base-layer fees and higher throughput options.

• But they should also monitor how quickly real-time proving solutions like Pico Prism move from testing → production → full node support.

• Projects targeting L1 might see fewer scalability constraints, but still need to account for transition risk.

• Hardware requirements may drop in the medium term (less need for full re-execution rigs).

• Opportunity for “light-node” or home-validation becomes more realistic — which could broaden participation and decentralisation.

• Providers of proving clusters (e.g., Brevis-type infra) may become new infrastructure players; risk of concentration needs monitoring.

• The shift toward ZK-proof-based validation shifts the paradigm: trust moves from raw compute to cryptographic validity. Governance and audits must adapt.

• Upgrades like EIP-7825 and roadmap changes will need coordination across clients, protocols, and validators.

• The economic model of Ethereum (fees, gas, block size) may evolve — fees may drop, but block size/gas limit decisions become more critical.

Pico Prism is by no means a silver bullet — but it represents a meaningful advance in the push toward Ethereum’s next growth phase. Its achievement — near-10-second proof times, consumer-hardware clusters, cost reduction — crosses several “hard lines” in Ethereum’s scaling challenge.

For participants — developers, validators, and investors alike — the takeaway is cautious optimism. The foundation for transformative change is taking shape, but execution, ecosystem alignment and decentralisation still need to be proven in real-world conditions. Real-time proving is not just a technical feat — it’s a critical enabler for Ethereum’s next chapter.

Disclaimer: This article is for informational and educational purposes only. It does not constitute financial advice or a recommendation to invest. The technologies, timelines and performance metrics described are subject to change and depend on many variables.