Cysic (@cysic_xyz): Cysic Open-Sources Venus zkVM: The Fastest ZK Proving Engine on Ethereum, Bar None

Cysic Open-Sources Venus zkVM: The Fastest ZK Proving Engine on Ethereum, Bar None Ethereum is quietly undergoing an infrastructure revolution. As ZK technology moves from research into production, the tradeoff between proving speed and cost is becoming the defining barrier to who can meaningfully participate in Ethereum's verification layer. Cysic – a full-stack integrator of ZK hardware acceleration and proving networks – has launched and open-sourced Venus, its next-generation zkVM compute engine. According to official @eth_proofs data, Venus ranks #1 in both proving efficiency and cost control on a single node, single GPU basis. Real-World Performance on Minimal Hardware The prevailing industry approach is to brute-force proving time by stacking large numbers of GPUs. Cysic takes a different path – optimizing architecture over raw compute, pushing single-node efficiency to its limits. According to Ethproofs data, Cysic Venus delivers exceptional single-node performance while dramatically lowering the barrier to running a proving node: Proving Speed: Venus achieves an average proving time of 1 minute 54 seconds on a single-node cluster, with a best recorded time of 1 minute 47 seconds on the Ethproofs platform – the fastest result in any public dataset. By comparison, SP1 averages 4 minutes 45 seconds and ZisK 0.16.1 averages 2 minutes 35 seconds on equivalent hardware. Venus is ~2.5× faster than SP1 and over 40 seconds faster than ZisK. Proving Cost: Venus averages $0.0192 per proof – less than half of ZisK 0.16.1 ($0.0404) and just one-quarter of SP1 ($0.0776). In Ethproofs benchmark conditions, this figure drops further to $0.0165. Stress Testing: On real proving workloads, a single previous-generation consumer GPU – the RTX 3090 – achieved an absolute time of 47.84 seconds. On the latest RTX 5090, OPT_LEVEL=1 delivers the optimal balance of speed and stability. Architectural Shift: From HAL to Graph Mainstream zkVM systems like RISC0 and SP1 typically use a HAL (Hardware Abstraction Layer) model, where the CPU drives the entire proving pipeline and calls GPU kernels only for compute-intensive operations. This design is portable across platforms, but has a clear downside: frequent CPU–GPU data synchronization wastes significant GPU cycles on waiting and communication rather than actual computation. Venus fundamentally restructures the entire ZK proving process as a dataflow computation graph. Rather than decomposing proofs into a sequence of function calls, Venus explicitly encodes the complete computational dependency graph before execution begins, allowing the GPU to schedule and execute autonomously. Key mechanisms include: Cross-kernel data placement: intermediate results remain resident in GPU VRAM, eliminating repeated host-device data transfers. cudaGraph capture and replay: high-frequency proving paths are captured as cudaGraph instances and replayed to eliminate scheduling overhead. The result is a dramatic increase in actual GPU utilization – not just peak theoretical throughput. Aligning with Ethereum's ZK Roadmap Cysic is listed as an Ethproofs community integration partner and will run directly as an Ethereum zkEVM node. As EIP-8025 advances, Ethereum's block verification layer is evolving into a global compute market. The Ethereum Foundation has set clear hardware targets: total cost under $100K, power consumption under 10kW, and the ability to cover 99% of blocks within 10 seconds. Venus is designed with exactly these goals in mind. By compressing proving node hardware requirements to 24 or fewer consumer-grade GPUs, small and mid-sized operators and independent developers gain a real path to participating in Ethereum's decentralized verification layer – directly aligned with Ethereum's long-term commitment to validator decentralization. On the engineering side, Venus is integrating with Flashbots' block-building infrastructure, rbuilder, using async buffering and preemption mechanisms to steadily dispatch proving tasks to underlying hardware without disrupting block production cadence. Laying the Groundwork for Custom Silicon The Graph architecture's value extends beyond today's GPU optimizations as a bridge toward custom hardware. Cysic has completed HLS prototype architecture validation on FPGA chips including the VU47P and VH1782. While clock speeds of 74–98 MHz mean a single FPGA cannot yet match a deeply optimized GPU in raw performance, the computation graph semantics have been validated across the full compilation path from graph description to hardware. Once the roadmap reaches ASIC, hardened hardware data paths will unlock step-change performance improvements. The logic: validate feasibility on GPU with the Graph architecture, then migrate computation to custom silicon using the same semantics – without rewriting the entire system. For now, single-node GPU remains the best production choice in terms of price-performance. But the graph-first architecture opens a complete path – from consumer hardware to custom silicon, from standalone nodes to a global proving market. Appendix: Cysic zkVM Trilogy (Part 1): Go Graph https://x.com/Cysic_CN/status/2028305924482629939 Cysic zkVM Trilogy (Part 2): Accelerating zkVM, Re-examining GPU, FPGA, and ASIC https://x.com/Cysic_CN/status/2029101905709023567 Cysic zkVM Trilogy (Part 3): Building Production-Grade zkEVM Nodes https://x.com/Cysic_CN/status/2031978251963548057