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Zcash Miners: Antminer Z15 and Z9 Profitability
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| Model |
Profitability
Profit
|
|---|---|
|
Bitmain Antminer Z15 Pro
Equihash · 840kSol/s
|
$40.70
/day
|
|
Bitmain Antminer Z15K
Equihash · 525kSol/s
|
$24.01
/day
|
|
Bitmain Antminer Z15
Equihash · 420kSol/s
|
$20.12
/day
|
|
Innosilicon A9 Plus Plus
Equihash · 140kSol/s
|
$4.70
/day
|
|
Innosilicon A9++ ZMaster
Equihash · 140KH/s
|
$4.70
/day
|
|
Bitmain Antminer Z11
Equihash · 135kSol/s
|
$4.68
/day
|
|
Bitmain Antminer Z11
Equihash · 135KH/s
|
$4.68
/day
|
|
Innosilicon A9 Plus
Equihash · 120kSol/s
|
$3.60
/day
|
|
Innosilicon A9
Equihash · 50kSol/s
|
$1.55
/day
|
|
Innosilicon A9 ZMaster
Equihash · 50KH/s
|
$1.55
/day
|
|
Bitmain Antminer Z9
Equihash · 42kSol/s
|
$0.44
/day
|
|
Bitmain Antminer Z9 Mini
Equihash · 10kSol/s
|
$-0.03
/day
|
Our cutting-edge mining calculator offers comprehensive insights across all major cryptocurrency algorithms, helping users easily identify the most profitable options for their specific hardware. The algorithm data is continuously refreshed to keep pace with the dynamic crypto mining industry, providing accurate evaluations based on real-time profitability statistics and overall market activity. This empowers users to make well-informed choices that reflect the latest mining conditions and algorithm performance.
How to read an Equihash miner's numbers
Equihash is a memory-hard proof of work introduced in 2016 by Alex Biryukov and Dmitry Khovratovich, and it draws on the generalized birthday problem through Wagner’s algorithm. The design forces miners to juggle large tables of partial collisions, so RAM capacity and bandwidth dominate performance. This favors GPUs with ample VRAM and wide buses, and it slows the early rise of specialized ASICs. Privacy-focused projects like Zcash, Horizen, and Komodo adopted it to broaden participation and to anchor censorship-resistant payments. Networks select parameter pairs such as 200_9, 192_7, and 210_9 to balance memory footprint, solver time, and verification cost. Full nodes verify proofs much faster than miners can find them, which preserves accessible validation on ordinary machines. ASICs have still emerged for some variants, so absolute resistance is difficult and decentralization remains a moving target. Solver engineering pushes hard on memory behavior with bucket sorting, parallel collision search, warp-level shuffles, and cache-friendly data layouts. Custom allocators and coalesced writes trim latency for intermediate states, and these gains compound on GPUs with high memory clocks. Practical tuning favors more VRAM, higher memory frequency, and stable thermals over raw core speed, and miners track throughput as solutions per second. Performance scales more with memory bandwidth than with arithmetic units, and that trait defines the economic edge for many rigs. The algorithm can require hundreds of megabytes to several gigabytes per instance depending on parameters, which can exclude low-end systems. Personalization fields bind solutions to a specific chain, so work cannot be recycled across networks. Difficulty retargeting and parameter choices aim to hold block times steady as hashpower shifts and they shape who can persist in the contest. Miners estimate returns with public profitability tools and weigh power draw against efficiency to judge viability, because in this arena where machines live or die by heat and watts, fear turns to prudence and fairness hardens into rule.
- Sol/s
- Solutions per second: one Equihash "hash" is a full solution to the puzzle, so the unit is deliberately different from H/s.
- kSol/s
- A thousand solutions per second. Today's Zcash ASICs are rated in the hundreds of kSol/s; the table shows the exact figure per miner.
- J/kSol
- Joules per thousand solutions, the efficiency figure to compare two Equihash miners with. Lower is better, exactly like J/TH on Bitcoin hardware.
- Network Sol/s
- The whole network's solve rate. Your miner's share of it is your share of every block reward, before pool fees.
What each kSol/s class earns at today's network solve rate
Gross Zcash per day before electricity and pool fees. The table above already nets out your power cost; this is the raw share of the block reward.
Coins the same Equihash parameters can mine. The table picks the best-paying one per miner.
Horizen Halvings, dev funds and the price of privacy
Zcash follows a Bitcoin-style schedule: roughly seventy-five-second blocks and a halving every four years, so an Equihash ASIC faces the same cliff a Bitcoin miner does. The difference is the split: a portion of every block funds Zcash development, and the miner's share is what the profit column is built on.
Equihash was designed to be memory-hard enough to favour graphics cards, and it did for a while. Dedicated Equihash ASICs then raised the network solve rate far beyond GPU reach, and the current generation runs at a fraction of the joules per kilosol of the first units. The efficiency column is where that shows.
Because the same Equihash parameters secure a handful of smaller chains, a Zcash miner is never locked to one coin. The family strip above lists them; when one pays better than Zcash at your rate, the table already reflects it.
Know your kSol/s and just want ZEC per day? Open the Zcash mining profitability calculator →
About the Equihash algorithm
Equihash, introduced in 2016 by cryptographers Alex Biryukov and Dmitry Khovratovich and grounded in the generalized birthday problem, defines its proof-of-work by a pair of adjustable parameters (n, k) that force miners to execute a sequence of collision-finding steps while retaining large sets of intermediate data in memory, so throughput hinges on RAM capacity, bandwidth, and cache locality rather than on raw arithmetic alone; this deliberate memory-hardness raises the cost of specialization, historically favoring well-equipped GPUs and general-purpose hardware, and it anchors verification in a compact, deterministic proof that nodes can check quickly using the same hash primitives (commonly BLAKE2b in deployed systems) without mirroring the miner’s heavy memory footprint, which helps keep block validation efficient even as the search itself remains data-hungry; networks have tuned (n, k) over time-moving between parameter sets such as those used by Zcash and its later iterations-to sustain decentralization pressure and blunt hardware monocultures, and researchers have explored hybrid consensus designs that embed Equihash as a PoW layer to complement proof-of-stake, thereby adding a tamper-resistant, memory-bound gate to block creation; in practice, the algorithm’s demand for hundreds of megabytes to several gigabytes of working memory per solver round transforms mining into an exercise in moving and organizing data at scale, and while this curbs trivial ASIC advantages, the eventual appearance of dedicated Equihash ASICs has underscored a broader reality: complete ASIC resistance is elusive, and parameter agility plus governance must do the ongoing work of defense; still, by translating cryptographic theory into a puzzle where collisions, not just cycles, carry the rhythm of difficulty, Equihash has remained a reference point for memory-hard proof-of-work, powering privacy-focused networks such as Zcash, Horizen, and Komodo, encouraging wider participation where high-memory rigs are accessible, yet candid about the trade-off that steep memory requirements can pose for smaller miners, and standing as a sobering, durable benchmark in the continuing negotiation between open participation and hardware centralization.
Zcash ASIC mining, answered
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