gmsor legend. @cysic_xyz is advocating a full-stack approach based on hardware acceleration in the Zero-Knowledge (ZK) infrastructure space. By combining self-designed ASICs and optimized GPU stacks with a distributed prover network and a dedicated consensus and settlement layer (a chain based on Cosmos SDK), it differentiates itself from existing software-centric projects. According to the disclosed figures, 1.36 million participants were involved in the testnet, generating over 7 million proofs, and attracting a cumulative investment of 18 million dollars. The project is concurrently working on a ComputeFi model (digital compute cube) that tokenizes computational resources for monetization based on this infrastructure. From an architectural perspective, Cysic aims for a hybrid structure that uses a consensus mechanism called 'Proof-of-Compute' to employ computation puzzles of proof-of-work nature in prover competitions, concluding finality with stake-based validation. It is explained that fairness in task allocation is secured using VRF, and around 41,800 active provers were observed in the testnet. Performance advantages include accelerating core ZK operations like Keccak and MSM/NTT with ASIC and CUDA kernels, achieving proof speeds 52–100 times faster than CPUs, and reducing verification costs by up to 90%. This is significant for high-load workloads such as rollups, bridges, and ZKML (verifiable AI inference). In the competitive landscape, Aleo and Mina are already operating mainnets as privacy L1 and lightweight zero-knowledge chains, leveraging software abstraction and accessibility as their strengths. Giza specializes in ZKML and agent orchestration on Starknet. Cysic differentiates itself by vertically integrating hardware and networks compared to these projects and is optimized for large-scale parallel proofs targeting high throughput and enterprise demand. However, since Cysic is still in the pre-mainnet stage, further validation of stability and economic viability in real operational environments is necessary. The ComputeFi model tokenizes physical computational resources (GPU/ASIC) into shares (digital compute cubes) to distribute profits. Cube holders receive proportional distributions of profits generated from ZK proofs, AI inference, and certain mining tasks. It is estimated that 21,392 cubes were claimed in the August 2025 sale, resulting in an influx of initial funding worth millions of dollars. The goal of this model is to convert idle hardware into verifiable production assets on-chain. From a demand perspective, theoretically, an annual demand for ZK proofs is predicted to be around 87 to 90 billion by 2030, with verifiable AI (model integrity and output proof) and privacy-preserving computations (medical and financial data processing) also mentioned as growth drivers. Cysic has disclosed partnerships with Scroll, Succinct, and Herodotus, suggesting applicability in the rollup and co-processor fields. Testnet metrics (participant scale, proof count, prover composition) demonstrate potential processing capabilities, but it remains to be seen whether economic incentives can offset real costs (hardware depreciation and electricity costs) over the long term after the mainnet launch. Risk factors can be summarized into three axes. First, there is the hardware adoption barrier. The upfront investment costs for acceleration devices, personnel constraints in operating CUDA and ZK stacks, and the volatility of electricity costs may limit the speed of prover expansion. Second, there is competition with software-centric alternatives. zkVM, STARK series, and ZK services from cloud providers have fast release and update cycles, and enterprise customers tend to prefer low-latency and existing certification systems (SOC2/ISO, etc.). Third, there is the risk of pre-mainnet execution. Market validation of tokenomics, sustainability of actual demand (proof order volume), security (side-channel and circuit vulnerabilities), and network survivability (prover collusion and availability) will only become clear during the operational phase. In summary, Cysic is attempting to improve the cost structure and processing limits of ZK infrastructure through a vertically integrated strategy of hardware acceleration + distributed prover market + dedicated chain. The testnet figures and partnerships support the technological and market potential, but since it is still in the pre-mainnet stage, demonstrating performance, security, and economic viability is the top priority. There is a high likelihood of showing strengths in areas where performance can offset costs, such as rollup proofs requiring high throughput, near-real-time verifiable AI inference, and regulation-friendly privacy computations. Conversely, for small-scale and lightweight workloads that prioritize developer-friendliness and general accessibility, a software-first approach may be more advantageous. The future success will likely depend on securing a critical mass of hardware networks (e.g., tens of thousands to hundreds of thousands of GPU-level devices), stable generation of proof demand, and maintaining a continuous advantage in chip and software optimization.