Today's Cryptocurrency Prices by Market Caps
The global cryptocurrency market cap today i $2.35T
Market Cap
$2.35T
24h Trading Volume
$141.09B
BTC Dominance
56.47%
|
#
|
Name
|
Price
|
1h %
|
24h %
|
7d %
|
Market Cap
|
Volume (24h)
|
Chart (7d) |
|---|---|---|---|---|---|---|---|---|
|
|
—
|
|||||||
|
No cryptocurrencies found Try adjusting your search query |
||||||||
Latest Crypto News
View All News
Smart-contract and DeFi coins lead losses as bitcoin wilts for 4th straight day
Concerns about STRC, the dividend-paying preferred stock from Strategy continue to dominate market sentiment.
Bitcoin tipped for Q3 'macro bottom' near $50K as major liquidity grab looms
Bitcoin market participants may be left in "complete disbelief" as the market reverses from a liquidity grab without another major leg lower, a trader predicted.
HIVE Wins $220M Bell‑Cohere Contract to Host 2,304 GPUs, Cementing Its Pivot to AI Infrastructure
HIVE Digital Technologies surged more than 7% Thursday after landing a landmark $220 million GPU cloud contract with Bell Canada and Toronto-based AI firm Cohere—marking the company’s biggest non-crypto deal to date and a clear signal that HIVE has moved decisively into AI infrastructure. The three-year agreement is being delivered by HIVE’s BUZZ High Performance Computing subsidiary and will place 2,304 NVIDIA Grace Blackwell GPUs—chips built for cutting‑edge AI model training and inference—inside Bell’s purpose-built data center in Merritt, British Columbia. Cohere, which builds large language models and enterprise AI systems, will use that compute layer to run its platform for Canadian customers, including government agencies that require on‑shore infrastructure. Why this matters - Sovereign AI: The contract plugs directly into Canada’s Sovereign AI push. Ottawa has committed more than $2 billion to domestic AI compute and invested roughly $240 million in Cohere. Running critical AI workloads on infrastructure inside national borders—and under local control—matters a lot for government and regulated clients. - Strategic anchor: Cohere, which recently announced a merger with Germany’s Aleph Alpha valuing the combined company at about $20 billion, was already partnered with Bell (since July 2025). This deal provides the physical compute layer for that relationship. HIVE’s pivot from Bitcoin mining to AI compute HIVE is no longer just a Bitcoin miner on paper: the company reported $278.3 million in Bitcoin mining revenue in its most recent quarter, but has been shifting capacity toward GPUs and AI since 2022. Recent moves include: - Redirecting GPU capacity from crypto mining - A GPU supply deal with Dell announced last November - A $115 million convertible note offering in April to fund additional hardware purchases HIVE says the Merritt deployment, expected to go live between late 2026 and early 2027, should add roughly $70 million in new annual recurring revenue on top of about $35 million it already earns from existing GPU operations—pushing its contracted high-performance computing (HPC) revenue above $100 million. Broader strategy and market context HIVE’s pivot mirrors a trend among former miners: Keel Infrastructure (ex-Bitfarms) recently sold its last Paraguay mining facility and is pursuing AI compute as well. The logic is straightforward—crypto mining returns can be volatile and compress during “crypto winters,” while AI compute demand is growing rapidly and often backed by multi‑year contracts, especially when government clients are involved. Looking ahead, HIVE has an even bigger build planned: a proposed 320‑megawatt AI data center in the Greater Toronto Area that could house more than 100,000 NVIDIA GPUs at full build‑out. The company projects roughly $360 million in annualized recurring revenue from that facility at capacity and has set a broader target of $660 million in annualized HPC revenue by the end of 2028. “This partnership with Bell and Cohere is a defining moment. BUZZ HPC is the GPU factory layer that transforms Canada’s AI ambitions from political promises into productive national assets,” HIVE executive chairman Frank Holmes said in a statement—framing the deal as both a commercial win and a national infrastructure milestone. Bottom line: The Bell-Cohere contract gives HIVE tangible, multi-year AI revenue and validates its strategy to redeploy crypto-era GPU capacity into a fast‑growing, sovereign‑sensitive market—while underscoring how miners are increasingly reshaping themselves as AI infrastructure providers. Read more AI-generated news on: undefined/news
Kentucky Sues Kalshi & Polymarket, Raising Stakes in CFTC vs. State Prediction-Market Battle
Kentucky has added its name to a growing list of states moving against prediction market platforms, filing suit this week against Kalshi and Polymarket and accusing them of operating illegal sportsbooks. “This multi-billion dollar corporations and their legal fictions don’t pass the sniff test,” Kentucky Attorney General Russell Coleman said, accusing both companies of running unlawful betting operations in the state. The complaint contends Kalshi and Polymarket skirt state gambling laws by failing to register as gambling operators and by not meeting obligations such as providing resources to address gambling addiction. Why this matters for crypto and prediction markets - The two platforms argue their contracts should be regulated as “swaps” under federal law and fall under the Commodity Futures Trading Commission’s (CFTC) jurisdiction rather than state gambling regulators. That federal-versus-state jurisdictional battle is the core legal flashpoint. - Regulators and courts nationwide are split on how to treat prediction-market bets that for many users resemble sports wagers. A resolution could reshape compliance regimes, licensing needs, and product design for prediction-market firms—many of which are popular among crypto-savvy traders. Where the fight stands - Kentucky’s suit follows similar actions in other states. The CFTC and Department of Justice have also pushed back against state-level regulation, leading to federal lawsuits challenging state attempts to rein in these platforms. - Federal courts are issuing mixed decisions. In the Sixth Circuit—which covers Kentucky, Ohio, Tennessee, and Michigan—two district judges have preliminarily sided with state regulators while another has sided with prediction markets. Those conflicting rulings increase the likelihood this dispute reaches the U.S. Supreme Court for a final, nationwide decision. Other targets and broader impact - Kentucky’s filing also names VGW, an online casino operator accused of running illegal sweepstakes in the state. - A Supreme Court or federal-circuit resolution would determine whether prediction markets must follow state gambling rules or can operate under federal CFTC oversight as swap markets. That outcome will affect product availability, KYC/AML and responsible-gambling obligations, and how crypto-native platforms structure derivatives and event contracts going forward. Bottom line This latest suit underscores rising regulatory pressure on prediction markets and highlights a high-stakes jurisdictional showdown that could reshape the industry. Crypto traders and market operators should watch upcoming appeals and circuit rulings closely—this dispute may ultimately set the rules for how prediction markets operate nationwide. Read more AI-generated news on: undefined/news
Z.AI's GLM-5.2: Nvidia-free, MIT-licensed LLM with 1M-token context - cheap boon for crypto devs
Z.AI’s new GLM-5.2 is here — and it’s turning heads for performance, price, and the chips it didn’t use. What happened - On June 16 Beijing-based Z.AI released GLM-5.2, a major upgrade over GLM-5.1. The announcement, coming after the recent U.S. ban on Anthropic’s Fable family, helped send Z.AI’s stock up roughly 90% to a fresh all-time high. - Z.AI has been on the U.S. Entity List since January 2025, making GLM-5.2’s arrival politically and commercially notable as an example of alternative AI supply chains. How it stacks up - FrontierSWE (dominance rate, large-scale technical projects): GLM-5.2 scored 74.4. Claude Opus 4.8: 75.1. GPT-5.5: 72.6. - SWE-bench Pro (real-world GitHub issue resolution, pass rate): GLM-5.2 scored 62.1, ahead of GPT-5.5’s 58.6 and far above GLM-5.1’s 58.4. - In the Artificial Analysis Intelligence Index (9 aggregated scores) GLM-5.2 becomes the best open-source model to date. OpenRouter benchmarks place it in the same performance class as the now-banned Claude Fable 5. - One remaining gap: on SWE-Marathon (sustained, hardest engineering tasks) GLM-5.2 scored 13.0 versus Opus 4.8’s 26.0 — the closed-source frontier still leads on the longest, heaviest workloads. Why the hardware angle matters - GLM-5.2 was trained on Huawei’s Ascend family (Ascend Atlas servers). There are no Nvidia chips in its pipeline — a meaningful point amid export controls and U.S.-China tech tensions. - Stability AI founder Emad Mostaque estimated total training costs at roughly $25 million, with about 80% of those costs in post-training — implying substantially lower training overhead than many peers. Model specs that developers care about - Size and architecture: 744-billion-parameter mixture-of-experts model. - Context window: a genuine 1,000,000-token window (up from GLM-5.1’s 200K). This enables single-call workflows for whole-repo navigation, multi-file refactors, and long agentic pipelines that previously required chunking. - License: weights released under the MIT license — broad reuse allowed and resistant to vendor or government “access switches.” Pricing and developer access - API pricing: $1.40 per million input tokens and $4.40 per million output tokens. For comparison, Claude Opus 4.8 lists $5 per million input and $25 per million output. - GLM Coding Plan starts at about $18/month and integrates with Claude Code, Cline, Kilo Code and popular agentic environments. - Free testing: GLM-5.2 is available for limited free trials on z.AI. Full open-source weights and the quantized variants are hosted on HuggingFace under the MIT license; Coding Plan users can call the model with the string GLM-5.2. Local deployment and quantization - Unsloth AI produced a 2-bit GGUF quantization that compresses the 1.51 TB model down to ~238 GB while retaining ~82% of its original accuracy. - Local running remains demanding: even the quantized build needs around 256 GB of unified memory or a RAM/VRAM combination capable of offloading MoE layers (examples include a maxed M4 Ultra Mac Studio or a workstation with ~256 GB system RAM and a mid-range GPU). - That makes self-hosting feasible for some teams and labs, but it’s still an expensive setup for casual users. Real-world feel - In a quick zero-shot test building a small game combining typing mechanics and shooter elements, GLM-5.2 produced the most varied gameplay states we’ve seen in this class of model — more scenario diversity and shifting enemy/boss behavior, though UI polish lagged behind some rivals. That strength in diversity maps to where GLM-5.2 is economically compelling: multi-shot generation workflows and agentic pipelines where varied outputs beat single-output polish. What it means for crypto and dev communities - Lower API costs and an MIT license make GLM-5.2 attractive to open-source projects, tooling developers, and teams building agentic or programmatic AI workflows — including tooling for smart contracts, audits, bot infrastructure, and developer automation. - The use of non-U.S. hardware and the model’s licensing raise strategic points about supply-chain diversification and resilience amid export controls and geopolitical friction. Bottom line GLM-5.2 is a leap forward for open-source large models: strong benchmark results, huge context windows, cheap-ish API pricing, and MIT-licensed weights. It doesn’t fully close the gap to the closed-source leaders on the longest engineering marathons, but it’s an important and commercially disruptive step — especially given it was built without Nvidia chips. The weights (and compressed variants) are on HuggingFace, available now for developers and teams to test and deploy. Read more AI-generated news on: undefined/news
Co-Director Hsiao-Wei Wang Resigns, Deepening Ethereum Foundation Leadership Shake-Up
Another senior leader has left the Ethereum Foundation, deepening questions about the organization’s future direction and capacity to steward the protocol. What happened - Hsiao-Wei Wang, a co-director at the Ethereum Foundation, announced via social media that she is stepping down effective immediately. Wang said the decision came after a recent sabbatical and credited interim co-director Bastian Aue for managing the transition “with care and thoughtfulness.” - Wang’s departure follows the February exit of her fellow co-director Tomasz Stańczak. After Stańczak left, Aue was named interim co-director alongside Wang. Context and leadership shake-up - Wang’s exit comes about a month after Ethereum co-founder Vitalik Buterin said the Foundation would transition to a “smaller ship,” refocusing resources on a narrower set of priorities: censorship resistance, privacy, and security. - The Foundation has already seen a string of notable exits in recent months, including top researcher Dankrad Feist, Stańczak, and at least two long-tenured staffers. Those departures have prompted public skepticism about whether the Foundation can continue to push the Ethereum ecosystem forward. Calls for a new structure - Concerns intensified when Feist suggested the community needs an entirely new organization with at least $1 billion in ETH funding to “save Ethereum.” On X, Feist argued the community needs an entity “economically aligned with Ethereum and accountable to it,” led by “a leader who is competent and wants to fight.” Organizational changes and treasury moves - Buterin has said the Foundation has been making “large changes” dating back to early 2025 to improve ties with ecosystem builders and active participants. Those reform efforts continued into 2026 as Ethereum reassesses its relationship with layer-2 networks. - The Foundation has also moved to be more transparent about its finances. It released a clearer treasury policy outlining when it would sell ETH and said it will aim to “earn acceptable returns on treasury assets.” Earlier this year, the Foundation began staking some of its holdings, with an eventual target of staking roughly 70,000 ETH — about $119 million at current prices. Market reaction - ETH was trading around $1,708 and was down about 1.4% in the last 24 hours. That price is roughly 66% below the token’s all-time high of $4,946 reached in August 2025. What’s next - The departures and strategic tightening leave open questions about how the Foundation will execute its narrowed mandate and whether new governance or funding models will emerge from the community. A representative for the Ethereum Foundation did not immediately respond to Decrypt’s request for comment. Read more AI-generated news on: undefined/news