Investors and traders seeking to understand divergent paths in technology and infrastructure sectors often compare CLSK and SNOW. CleanSpark operates as a Bitcoin miner evolving into a data center developer, while Snowflake provides a cloud-based data platform increasingly oriented toward artificial intelligence workloads. This comparison appeals to those evaluating growth potential in AI-related infrastructure versus enterprise software, as well as participants monitoring cryptocurrency correlations and consumption-based revenue models in the current market environment.
CleanSpark develops and operates data centers primarily for Bitcoin mining while advancing plans for AI and high-performance computing hosting. In recent weeks, the company reported fiscal third-quarter 2026 results showing revenue of $138 million, down year-over-year, and a net loss of $239.8 million influenced by a Bitcoin impairment charge. Sentiment has been shaped by a 20-year, $6.6 billion triple-net lease for an AI data center project, alongside ongoing Bitcoin price fluctuations. Stock behavior has featured sharp moves, with shares trading near $12 amid elevated volume and correlation to cryptocurrency markets, reflecting both the challenges of the mining business post-halving and opportunities in infrastructure diversification.
Snowflake delivers a cloud data platform that supports data warehousing, analytics, sharing, and AI applications across major public clouds. Recent market activity has highlighted continued product revenue growth around 30% year-over-year, fueled by AI features such as dynamic model routing. The stock has posted substantial year-to-date advances near 50%, trading around $328, supported by sector strength and customer expansion. Upcoming second-quarter fiscal 2027 results are anticipated amid analyst focus on consumption trends and margin dynamics. Performance reflects steady enterprise adoption rather than single-event volatility, with the company maintaining high net revenue retention rates.
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CLSK and SNOW operate in distinct areas of the technology landscape. CleanSpark’s business model centers on energy-intensive infrastructure with revenue tied to Bitcoin production and emerging leasing contracts, introducing higher beta to cryptocurrency cycles and project execution risks. Snowflake employs a consumption-based software model with recurring usage from enterprise clients, offering greater visibility into revenue growth but facing competition in the data platform space. Recent momentum favors SNOW through consistent AI-driven expansion, while CLSK exhibits sharper swings linked to Bitcoin and infrastructure announcements. Risk factors include regulatory and financing elements for CLSK versus valuation multiples and margin pressures for SNOW. Sector exposure places CLSK at the intersection of crypto and AI infrastructure, contrasting with SNOW’s positioning in enterprise cloud software.
Based on observable factors such as trend consistency, earnings stability, and positioning within AI-related growth areas, Tickeron’s AI models would currently assign a higher probability of favorable relative performance to SNOW. Its consumption-based model and repeated beats on growth metrics provide more predictable signals compared with CLSK’s greater exposure to commodity price movements and contract ramp timelines. This assessment remains probabilistic and subject to evolving market data.
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It is best to consider a long-term outlook for a ticker by using Fundamental Analysis (FA) ratings. The rating of 1 to 100, where 1 is best and 100 is worst, is divided into thirds. The first third (a green rating of 1-33) indicates that the ticker is undervalued; the second third (a grey number between 34 and 66) means that the ticker is valued fairly; and the last third (red number of 67 to 100) reflects that the ticker is undervalued. We use an FA Score to show how many ratings show the ticker to be undervalued (green) or overvalued (red).
CLSK’s FA Score shows that 0 FA rating(s) are green whileSNOW’s FA Score has 0 green FA rating(s).
It is best to consider a short-term outlook for a ticker by using Technical Analysis (TA) indicators. We use Odds of Success as the percentage of outcomes which confirm successful trade signals in the past.
If the Odds of Success (the likelihood of the continuation of a trend) for each indicator are greater than 50%, then the generated signal is confirmed. A green percentage from 90% to 51% indicates that the ticker is in a bullish trend. A red percentage from 90% - 51% indicates that the ticker is in a bearish trend. All grey percentages are below 50% and are considered not to confirm the trend signal.
CLSK’s TA Score shows that 4 TA indicator(s) are bullish while SNOW’s TA Score has 2 bullish TA indicator(s).
CLSK (@Investment Banks/Brokers) experienced а +8.83% price change this week, while SNOW (@Packaged Software) price change was +2.80% for the same time period.
The average weekly price growth across all stocks in the @Investment Banks/Brokers industry was +4.45%. For the same industry, the average monthly price growth was +13.06%, and the average quarterly price growth was +5.36%.
The average weekly price growth across all stocks in the @Packaged Software industry was -3.96%. For the same industry, the average monthly price growth was -2.40%, and the average quarterly price growth was +3.47%.
CLSK is expected to report earnings on Dec 16, 2026.
SNOW is expected to report earnings on Dec 02, 2026.
These banks specialize in underwriting (helping companies with debt financing or equity issuances), IPOs, facilitating mergers and other corporate reorganizations and acting as a broker or financial advisor for institutions. They might also trade securities on their own accounts. Investment banks potentially thrive on expanding its network of clients, since that could help them increase profits. Goldman Sachs, Morgan Stanley and CME Group Inc are some of the largest investment banking companies.
@Packaged Software (-3.96% weekly)Packaged software comprises multiple software programs bundled together and sold as a group. For example, Microsoft Office includes multiple applications such as Excel, Word, and PowerPoint. In some cases, buying a bundled product is cheaper than purchasing each item individually[s20] . Microsoft Corporation, Oracle Corp. and Adobe are some major American packaged software makers.
| CLSK | SNOW | CLSK / SNOW | |
| Capitalization | 3.26B | 119B | 3% |
| EBITDA | -572.87M | -813.42M | 70% |
| Gain YTD | 25.395 | 53.711 | 47% |
| P/E Ratio | 7.38 | N/A | - |
| Revenue | 679M | 5.44B | 12% |
| Total Cash | 795M | 2.35B | 34% |
| Total Debt | 1.79B | 2.76B | 65% |
CLSK | SNOW | ||
|---|---|---|---|
OUTLOOK RATING 1..100 | 50 | 50 | |
VALUATION overvalued / fair valued / undervalued 1..100 | 83 Overvalued | 93 Overvalued | |
PROFIT vs RISK RATING 1..100 | 100 | 86 | |
SMR RATING 1..100 | 98 | 98 | |
PRICE GROWTH RATING 1..100 | 50 | 37 | |
P/E GROWTH RATING 1..100 | 86 | 100 | |
SEASONALITY SCORE 1..100 | 90 | 50 |
Tickeron ratings are formulated such that a rating of 1 designates the most successful stocks in a given industry, while a rating of 100 points to the least successful stocks for that industry.
CLSK's Valuation (83) in the null industry is in the same range as SNOW (93) in the Other Consumer Services industry. This means that CLSK’s stock grew similarly to SNOW’s over the last 12 months.
SNOW's Profit vs Risk Rating (86) in the Other Consumer Services industry is in the same range as CLSK (100) in the null industry. This means that SNOW’s stock grew similarly to CLSK’s over the last 12 months.
SNOW's SMR Rating (98) in the Other Consumer Services industry is in the same range as CLSK (98) in the null industry. This means that SNOW’s stock grew similarly to CLSK’s over the last 12 months.
SNOW's Price Growth Rating (37) in the Other Consumer Services industry is in the same range as CLSK (50) in the null industry. This means that SNOW’s stock grew similarly to CLSK’s over the last 12 months.
CLSK's P/E Growth Rating (86) in the null industry is in the same range as SNOW (100) in the Other Consumer Services industry. This means that CLSK’s stock grew similarly to SNOW’s over the last 12 months.
| CLSK | SNOW | |
|---|---|---|
| RSI ODDS (%) | N/A | 5 days ago 77% |
| Stochastic ODDS (%) | 5 days ago 86% | 5 days ago 79% |
| Momentum ODDS (%) | 5 days ago 89% | 5 days ago 76% |
| MACD ODDS (%) | 5 days ago 85% | 5 days ago 76% |
| TrendWeek ODDS (%) | 5 days ago 87% | 5 days ago 77% |
| TrendMonth ODDS (%) | 5 days ago 90% | 5 days ago 75% |
| Advances ODDS (%) | 5 days ago 88% | N/A |
| Declines ODDS (%) | 8 days ago 88% | 7 days ago 77% |
| BollingerBands ODDS (%) | N/A | 5 days ago 73% |
| Aroon ODDS (%) | 5 days ago 90% | 5 days ago 73% |
| 1 Day | |||
|---|---|---|---|
| ETFs / NAME | Price $ | Chg $ | Chg % |
| OKLL | 2.51 | 0.16 | +6.81% |
| Defiance Daily Target 2X Long OKLO ETF | |||
| HYEM | 19.97 | 0.01 | +0.05% |
| VanEck EM High Yield Bond ETF | |||
| USCA | 45.93 | N/A | N/A |
| Xtrackers MSCI USA Clmt Actn Eq ETF | |||
| OPPG | 38.18 | N/A | N/A |
| WisdomTree GeoAlpha Opportunities Fund | |||
| TGLR | 40.29 | -0.12 | -0.29% |
| Wedbush Laffer Tengler New Era Value ETF | |||
A.I.dvisor indicates that over the last year, CLSK has been closely correlated with MARA. These tickers have moved in lockstep 84% of the time. This A.I.-generated data suggests there is a high statistical probability that if CLSK jumps, then MARA could also see price increases.
| Ticker / NAME | Correlation To CLSK | 1D Price Change % | ||
|---|---|---|---|---|
| CLSK | 100% | +0.87% | ||
| MARA - CLSK | 84% Closely correlated | -2.50% | ||
| RIOT - CLSK | 81% Closely correlated | +3.12% | ||
| BTBT - CLSK | 77% Closely correlated | +0.61% | ||
| KEEL - CLSK | 76% Closely correlated | +3.58% | ||
| HUT - CLSK | 75% Closely correlated | +6.19% | ||
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A.I.dvisor indicates that over the last year, SNOW has been closely correlated with MDB. These tickers have moved in lockstep 67% of the time. This A.I.-generated data suggests there is a high statistical probability that if SNOW jumps, then MDB could also see price increases.
| Ticker / NAME | Correlation To SNOW | 1D Price Change % | ||
|---|---|---|---|---|
| SNOW | 100% | -5.41% | ||
| MDB - SNOW | 67% Closely correlated | -4.09% | ||
| COIN - SNOW | 63% Loosely correlated | -4.18% | ||
| NET - SNOW | 62% Loosely correlated | -1.96% | ||
| CLSK - SNOW | 61% Loosely correlated | +0.87% | ||
| NOW - SNOW | 56% Loosely correlated | -2.97% | ||
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