Gcore has expanded the regional coverage of its cloud services, including Infrastructure as a Service, AI IPU Infrastructure, Logging as a Service, and Managed Kubernetes. New points of presence are located in the US, Asia, and EMEA. Read on to learn more about the services and their locations.
IaaS: 23 Locations
As an IaaS (Infrastructure as a Service) provider, Gcore offers virtual machines, bare metal servers, S3 storage, load balancing, and other cloud services. With Gcore’s IaaS, you get all the necessary building blocks for your cloud infrastructure.
In May 2023, we added new points of presence in Dubai (UAE) and Newport (UK.) The total list of Gcore Cloud PoPs comprises 23 locations across the Americas, Asia, Africa, and EMEA.
AI IPU infrastructure: 3 Locations
Gcore also provides AI Infrastructure as a Service based on Graphcore IPUs. AI IPU infrastructure speeds up machine learning and produces outstanding results for language processing, visual computing, and graph neural networks.
AI IPU infrastructure is now available in Luxembourg, Amsterdam, and Newport.
LaaS: 2 Locations
LaaS (Logging as a Service) is a cloud log management platform designed to collect, store, process, and analyze logs from infrastructure and applications. LaaS makes it easier to analyze events and data from multiple services in a single dashboard. With Gcore’s LaaS, you can detect and resolve errors in your infrastructure, investigate security incidents, check server connectivity, and more.
LaaS is available in Luxembourg and Manassas.
FaaS: 9 Locations
FaaS (Function as a Service) is a cloud service that lets you run code without worrying about the underlying infrastructure. You simply write a discrete piece of code called “function” and deploy it in our cloud environment. A function runs on demand, and you are charged only for its execution. FaaS helps to save costs on deploying a simple application, expanding functionality, and reducing time-to-market.
FaaS is now available in core regions in addition to edge regions. Here is the complete list of locations:
- Luxembourg
- Luxembourg-2
- Manassas
- Singapore
- Tokyo
- Santa Clara
- Frankfurt
- Istanbul
- Chicago
Managed Kubernetes: 4 Locations
Managed Kubernetes is a platform service that allows you to quickly and easily deploy a prebuilt Kubernetes cluster based on Gcore Cloud resources. Gcore’s team is responsible for maintaining the infrastructure and cluster, so you can quickly launch and easily scale your containerized applications.
The list of the Managed Kubernetes locations includes:
- Luxembourg
- Manassas
- Singapore
- Frankfurt
Gcore Basic: 5 Locations
Gcore Basic is a low-cost virtual machine with partial CPU usage. It is suitable for simple tasks such as hosting a website or blog, running a pet project, and deploying a private VPN. Gcore Basic is a great solution for home users, developers, and small business owners. You can deploy a virtual machine in a couple of minutes and integrate it with any Gcore Cloud service. Benefits include the latest Intel® Xeon® 4314 CPU, free built-in DDoS protection, and free egress traffic.
The list of the Gcore Basic locations includes:
- Frankfurt
- Amsterdam
- Manassas
- Hong Kong
- Tokyo
Take Advantage of Gcore’s Cloud Services
By expanding our regional coverage, we aim to improve the cloud experience for our customers, provide advanced IaaS and PaaS services anywhere, and enable global companies to achieve scalability across their distributed services and teams. Gcore’s network consists of 140+ points of presence worldwide, including 23 unique cloud locations. We are constantly enhancing our services for the convenience and efficiency of our customers, regardless of their location.
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Securing vibe coding: balancing speed with cybersecurity
Vibe coding has emerged as a cultural phenomenon in 2025 software development. It’s a style defined by coding on instinct and moving fast, often with the help of AI, rather than following rigid plans. It lets developers skip exhaustive design phases and dive straight into building, writing code (or prompting an AI to write it) in a rapid, conversational loop. It has caught on fast and boasts a dedicated following of developers hosting vibe coding game jams.So why all the buzz? For one, vibe coding delivers speed and spontaneity. Enthusiasts say it frees them to prototype at the speed of thought, without overthinking architecture. A working feature can be blinked into existence after a few AI-assisted prompts, which is intoxicating for startups chasing product-market fit. But as with any trend that favors speed over process, there’s a flip side.This article explores the benefits of vibe coding and the cybersecurity risks it introduces, examines real incidents where "just ship it" coding backfired, and outlines how security leaders can keep up without slowing innovation.The upside: innovation at breakneck speedVibe coding addresses real development needs and has major benefits:Allows lightning-fast prototyping with AI assistance. Speed is a major advantage, especially for startups, and allows faster validation of ideas and product-market fit.Prioritizes creativity over perfection, rewarding flow and iteration over perfection.Lowers barriers to entry for non-experts. AI tooling lowers the skill floor, letting more people code.Produces real success stories, like a game built via vibe coding hitting $1M ARR in 17 days.Vibe coding aligns well with lean, agile, and continuous delivery environments by removing overhead and empowering rapid iteration.When speed bites backVibe coding isn’t inherently insecure, but the culture of speed it promotes can lead to critical oversights, especially when paired with AI tooling and lax process discipline. The following real-world incidents aren’t all examples of vibe coding per se, but they illustrate the kinds of risks that arise when developers prioritize velocity over security, skip reviews, or lean too heavily on AI without safeguards. These three cases show how fast-moving or under-documented development practices can open serious vulnerabilities.xAI API key leak (2025)A developer at Elon Musk’s AI company, xAI, accidentally committed internal API keys to a public GitHub repo. These keys provided access to proprietary LLMs trained on Tesla and SpaceX data. The leak went undetected for two months, exposing critical intellectual property until a researcher reported it. The error likely stemmed from fast-moving development where secrets were hardcoded for convenience.Malicious NPM packages (2024)In January 2024, attackers uploaded npm packages like warbeast2000 and kodiak2k, which exfiltrated SSH keys from developer machines. These were downloaded over 1,600 times before detection. Developers, trusting AI suggestions or searching hastily for functionality, unknowingly included these malicious libraries.OpenAI API key abuse via Replit (2024)Hackers scraped thousands of OpenAI API keys from public Replit projects, which developers had left in plaintext. These keys were abused to access GPT-4 for free, racking up massive bills for unsuspecting users. This incident shows how projects with weak secret hygiene, which is a risk of vibe coding, become easy targets.Securing the vibe: smart risk mitigationCybersecurity teams can enable innovation without compromising safety by following a few simple cybersecurity best practices. While these don’t offer 100% security, they do mitigate many of the major vulnerabilities of vibe coding.Integrate scanning tools: Use SAST, SCA, and secret scanners in CI/CD. Supplement with AI-based code analyzers to assess LLM-generated code.Shift security left: Embed secure-by-default templates and dev-friendly checklists. Make secure SDKs and CLI wrappers easily available.Use guardrails, not gates: Enable runtime protections like WAF, bot filtering, DDoS defense, and rate limiting. Leverage progressive delivery to limit blast radius.Educate, don’t block: Provide lightweight, modular security learning paths for developers. Encourage experimentation in secure sandboxes with audit trails.Consult security experts: Consider outsourcing your cybersecurity to an expert like Gcore to keep your app or AI safe.Secure innovation sustainably with GcoreVibe coding is here to stay, and for good reason. It unlocks creativity and accelerates delivery. But it also invites mistakes that attackers can exploit. Rather than fight the vibe, cybersecurity leaders must adapt: automating protections, partnering with devs, and building a culture where shipping fast doesn't mean shipping insecure.Want to secure your edge-built AI or fast-moving app infrastructure? Gcore’s Edge Security platform offers robust, low-latency protection with next-gen WAAP and DDoS mitigation to help you innovate confidently, even at speed. As AI and security experts, we understand the risks and rewards of vibe coding, and we’re ideally positioned to help you secure your workloads without slowing down development.Into vibe coding? Talk to us about how to keep it secure.

Qwen3 models available now on Gcore Everywhere Inference
We’ve expanded our model library for Gcore Everywhere Inference with three powerful additions from the Qwen3 series. These new models bring advanced reasoning, faster response times, and even better multilingual support, helping you power everything from chatbots and coding tools to complex R&D workloads.With Gcore Everywhere Inference, you can deploy Qwen3 models in just three clicks. Read on to discover what makes Qwen3 special, which Qwen3 model best suits your needs, and how to deploy it with Gcore today.Introducing the new Qwen3 modelsQwen3 is the latest evolution of the Qwen series, featuring both dense and Mixture-of-Experts (MoE) architectures. It introduces dual-mode reasoning, letting you toggle between “thinking” and “non-thinking” modes to balance depth and speed:Thinking mode (enable_thinking=True): The model adds a <think>…</think> block to reason step-by-step before generating the final response. Ideal for tasks like code generation or math where accuracy and logic matter.Non-thinking mode (enable_thinking=False): Skips the reasoning phase to respond faster. Best for straightforward tasks where speed is a priority.Model sizes and use casesWith three new sizes available, you can choose the level of performance required for your use case:Qwen3-14B: A 14B parameter model tuned for responsive, multilingual chat and instruction-following. Fast, versatile, and ready for real-time applications with lightning-fast responses.Qwen3-30B-A3B: Built on the Arch-3 backbone, this 30B model offers advanced reasoning and coding capabilities. It’s ideal for applications that demand deeper understanding and precision while balancing performance. It provides high-quality output with faster inference and better efficiency.Qwen3-32B: The largest Qwen3 model yet, designed for complex, high-performance tasks across reasoning, generation, and multilingual domains. It sets a new standard for what’s achievable with Gcore Everywhere Inference, delivering exceptional results with maximum reasoning power. Ideal for complex computation and generation tasks where every detail matters.ModelArchitectureTotal parametersActive parametersContext lengthBest suited forQwen3-14BDense14B14B128KMultilingual chatbots, instruction-following tasks, and applications requiring strong reasoning capabilities with moderate resource consumption.Qwen3-30B-A3BMoE30B3B128KScenarios requiring advanced reasoning and coding capabilities with efficient resource usage; suitable for real-time applications due to faster inference times.Qwen3-32BDense32B32B128KHigh-performance tasks demanding maximum reasoning power and accuracy; ideal for complex R&D workloads and precision-critical applications.How to deploy Qwen3 models with Gcore in just a few clicksGetting started with Qwen3 on Gcore Everywhere Inference is fast and frictionless. Simply log in to the Gcore Portal, navigate to the AI Inference section, and select your desired Qwen3 model. From there, deployment takes just three clicks—no setup scripts, no GPU wrangling, no DevOps overhead. Check out our docs to discover how it works.Deploying Qwen3 via the Gcore Customer Portal takes just three clicksPrefer to deploy programmatically? Use the Gcore API with your project credentials. We offer quick-start examples in Python and cURL to get you up and running fast.Why choose Qwen3 + Gcore?Flexible performance: Choose from three models tailored to different workloads and cost-performance needs.Immediate availability: All models are live now and deployable via portal or API.Next-gen architecture: Dense and MoE options give you more control over reasoning, speed, and output quality.Scalable by design: Built for production-grade performance across industries and use cases.With the latest Qwen3 additions, Gcore Everywhere Inference continues to deliver on performance, scalability, and choice. Ready to get started? Get a free account today to explore Qwen3 and deploy with Gcore in just a few clicks.Sign up free to deploy Qwen3 today

Run AI workloads faster with our new cloud region in Southern Europe
Good news for businesses operating in Southern Europe! Our newest cloud region in Sines, Portugal, gives you faster, more local access to the infrastructure you need to run advanced AI, ML, and HPC workloads across the Iberian Peninsula and wider region. Sines-2 marks the first region launched in partnership with Northern Data Group, signaling a new chapter in delivering powerful, workload-optimized infrastructure across Europe.Strategically positioned in Portugal, Sines-2 enhances coverage in Southern Europe, providing a lower-latency option for customers operating in or targeting this region. With the explosive growth of AI, machine learning, and compute-intensive workloads, this new region is designed to meet escalating demand with cutting-edge GPU and storage capabilities.Built for AI, designed to scaleSines-2 brings with it next-generation infrastructure features, purpose-built for today’s most demanding workloads:NVIDIA H100 GPUs: Unlock the full potential of AI/ML training, high-performance computing (HPC), and rendering workloads with access to H100 GPUs.VAST NFS (file sharing protocol) support: Benefit from scalable, high-throughput file storage ideal for data-intensive operations, research, and real-time AI workflows.IaaS portfolio: Deploy Virtual Machines, manage storage, and scale infrastructure with the same consistency and reliability as in our flagship regions.Organizations operating in Portugal, Spain, and nearby regions can now deploy workloads closer to end users, improving application performance. For finance, healthcare, public sector, and other organisations running sensitive workloads that must stay within a country or region, Sines-2 is an easy way to access state-of-the-art GPUs with simplified compliance. Whether you're building AI models, running simulations, or managing rendering pipelines, Sines-2 offers the performance and proximity you need.And best of all, servers are available and ready to deploy today.Run your AI workloads in Portugal todayWith Sines-2 and our partnership with Northern Data Group, we’re making it easier than ever for you to run AI workloads at scale. If you need speed, flexibility, and global reach, we’re ready to power your next AI breakthrough.Unlock the power of Sines-2 today

Edge Cloud news: more regions and volume options available
At Gcore, we’re committed to delivering high-performance, globally distributed infrastructure that adapts to your workloads—wherever they run. This month, we’re excited to share major updates to our Edge Cloud platform: two new cloud IaaS regions in Europe and expanded storage options in São Paulo.New IaaS regions in Luxembourg and Portugal available nowLuxembourg‑3 and Sines‑2 mark the next step in the Gcore mission to bring compute closer to users. From compliance-focused deployments in Central Europe to GPU‑powered workloads in the Iberian Peninsula, these new regions are built to support diverse infrastructure needs at scale.Luxembourg‑3: expanding connectivity in Central EuropeWe’re expanding our European footprint by opening an additional IaaS point of presence (PoP) in Luxembourg. Strategically located in the heart of Europe, this region offers low-latency connectivity across the EU and is a strong compliance choice for data residency requirements.Here’s what’s available in Luxembourg‑3:Virtual Machines: High-performance, reliable, and scalable compute power for a wide range of workloads - with free egress traffic and pay-as-you-go billing for active instances only.Volumes: Standard, High IOPS, and Low Latency block storage for any workload profile.Load Balancers: Distribute traffic intelligently across instances to boost availability, performance, and fault tolerance.Managed Kubernetes: Fully managed Kubernetes clusters with automated provisioning, scaling, and updates optimized for production-ready deployments.Sines‑2, Portugal: a new hub for Southern Europe and a boost for AI workloadsWe’re also opening a brand-new location: Sines‑2, Portugal. This location enhances coverage across Southern Europe and boosts our AI and compute capabilities with more GPU availability.In addition to offering the same IaaS services as Luxembourg‑3, Sines‑2 also includes:H100 NVIDIA GPUs for AI/ML, high-performance computing, and rendering workloads.New VAST NFS Fileshare support for scalable, high-throughput file storage.This new region is ideal for organizations looking to deploy close to the Iberian Peninsula, reducing latency for regional users while gaining access to powerful GPU resources.Enhanced volume types in São PauloVolumes are the backbone of any cloud workload. They store the OS, applications, and essential data for your virtual machines. Developers and businesses building latency-sensitive or I/O-intensive applications now have more options in the São Paulo-2 region, thanks to two newly added volume types optimized for speed and responsiveness:Low-latency volumesDesigned for applications where every millisecond matters, Low Latency Volumes are non-redundant block storage ideal for:ETCD clustersTransactional databasesOther real-time, latency-critical workloadsBy minimizing overhead and focusing on speed, this volume type delivers faster response times for performance-sensitive use cases. This block storage offers IOPS up to 5000 and an average latency of 300 microseconds.High-IOPS volumesFor applications that demand both speed and resilience, High IOPS Volumes offer a faster alternative to our Standard Volumes:Higher IOPS and increased throughputSuitable for high-traffic web apps, analytics engines, and demanding databasesThis volume type accelerates data-heavy workloads and keeps performance consistent under peak demand by delivering significantly higher throughput and IOPS. The block storage offers IOPS up to 9,000 and a 500 MB/s bandwidth limit.Ready to deploy with Gcore?These new additions help to fine-tune your performance strategy, whether you're optimizing for throughput, latency, or both.From scaling in LATAM to expanding into the EU or pushing performance at the edge, Gcore continues to evolve with your needs. Explore our new capabilities in Luxembourg‑3, Sines‑2, and São Paulo‑2.Discover more about Gcore Cloud Edge Services

How AI is improving L7 DDoS protection solutions
How AI is improving L7 DDoS protection solutionsDDoS attacks have always been a concern for organizations, but with the recent rise of AI and machine learning, the threat has grown. Layer 7 attacks are particularly damaging, as they focus on the application layer that users utilize to interact with your system. Unlike traditional DDoS attacks, which aim to overwhelm the servers with sheer traffic, these advanced threats imitate real user behavior, making it incredibly difficult for defenses to identify and block malicious traffic.While this challenge is complex, it is far from insurmountable. In this situation, the mantra "fight fire with fire" really applies. By using machine learning and AI against AI-based attacks, organizations can then retaliate with equally advanced Layer 7 protection. These newer technologies can offer something beyond what more traditional techniques could hope to achieve, including significantly faster response times, smarter threat detection, and precision. Here’s how AI and ML are redefining how businesses stay online and secure.Why L7 DDoS attacks are dangerous and hard to stopL7 DDoS attacks are sneaky. Unlike network-based attacks that flood your bandwidth, these attacks go after your application logic. Picture thousands of fake users trying to log in, search for products, or complete transactions all at once. Your systems become overwhelmed, not because they’re receiving a massive amount of data, but because they’re handling what looks like genuine traffic.The big challenge is filtering out the bad traffic while letting legitimate users through. After all, if you accidentally block real customers, you’re essentially doing the attackers’ job for them.Manual defenses used in the past, such as rate limiting with static thresholds, can result in a lose-lose situation. When the threshold is set too high, attackers can enter, often in place of traditional users. If the threshold is set too low, legitimate users are left unable to access the application. This acts as a collective punishment, blocking users out of fear of a few malicious actors rather than an accurate solution that can identify the malicious activity and block it without compromising users’ experience. Traditional defenses, based on static rules or human intervention, simply cannot scale at the speed and intricacy of a modern attack. They’re reactive when they need to be proactive.Filtering traffic without blocking customersAI and ML avoid the pitfalls of traditional security systems by continuously analyzing traffic and identifying anomalies dynamically. One of the biggest pain points in DDoS defense is false positives, which block legitimate users because their behavior looks suspicious.Traditional solutions relying on static rules simply block any IPs displaying suspicious behavior, while AI and ML track the activity of IPs over time, building a detailed profile of legitimate traffic. Sometimes referred to as IP profiling, this process groups together the IP addresses that interact predictably and legitimately with your systems. By analyzing both current and historical data, these systems can differentiate suspicious IPs from legitimate users. In the event of an attack, “safe” IPs are automatically allowed through, while suspicious ones are challenged or blocked.These AI systems learn over time from previous attacks they’ve encountered, adapting for greater accuracy without any manual updating or intervention to counter-changing tactics. This allows the systems to correlate current traffic with historical profiles and continuously reassess the safety of certain profiles. This ensures that legitimate accounts can continue to access services unimpeded while malicious traffic is contained.Traditional systems cannot achieve this level of precision, and instead tend to shut down applications during attacks, essentially allowing the attackers to win. With advanced AI and ML based defenses, businesses can maintain their service undisturbed for real users, even during an attack.Fighting AI attacks with AI defensesDDoS attacks are becoming increasingly adaptive, using AI to mimic real users, leaving the static rules in traditional solutions unable to identify the subtle signs of attack traffic. Attackers constantly change their methods to avoid fixed security rules. Manually updating defenses each time a new attack method pops up is time-consuming and inefficient.AI-powered solutions overcome this limitation by using the same strategy as attackers, continuously learning from data input to adapt to increasingly convincing DDoS traffic in real time. This can stop even zero-day and self-evolving AI cyberattacks.Staying Ahead of Attackers With Smarter DefensesOur AI-driven WAAP solution delivers intelligent, interconnected protection, enabling businesses to stay ahead of even the most advanced and evolving threats, including L7 DDoS attacks. By leveraging deep traffic analysis, heuristic tagging, and adaptive learning, it provides a proactive defense strategy. With cross-domain capabilities and actionable security insights, Gcore WAAP is an essential asset for security architects and key decision-makers, seamlessly blending innovation with practicality to meet the demands of today’s digital landscape.Interested in exploring WAAP further? Download our ebook to discover cybersecurity best practices, the most prevalent threats, and how WAAP can protect your business’s digital infrastructure. Or, reach out to our team to learn more about Gcore WAAP.Discover why WAAP is a must-have for modern businesses—get your free ebook

How AI is transforming gaming experiences
AI is reshaping how games are played, built, and experienced. Although we are in a period of flux where the optimal combination of human and artificial intelligence is still being ironed out, the potential for AI to greatly enhance both gameplay and development is clear.PlayStation CEO Hermen Hulst recently emphasized the importance of striking the right balance between the handcrafted human touch and the revolutionary advances that AI brings. AI will not replace the decades of design, storytelling, and craft laid down by humans—it will build on that foundation to unlock entirely new possibilities. In addition to an enhanced playing experience, AI is shaking up gaming aspects such as real-time analytics, player interactions, content generation, and security.In this article, we explore three specific developments that are enriching gaming storyworlds, as well as the technology that’s bringing them to life and what the future might hold.#1 Responsive NPC behavior and smarter opponentsAI is evolving to create more realistic, adaptive, and intelligent non-player characters (NPCs) that can react to individual player choices with greater depth and reasoning. The algorithms allow NPCs to respond dynamically to players’ decisions so they can adjust their strategies and behaviors in real time. This provides a more immersive and dynamic gameplay environment and means gamers have endless opportunities to experience new gaming adventures and write their own story every time.A recent example is Red Dead Redemption 2, which enables players to interact with NPCs in the Wild West. Players were impressed by its complexity and the ability to interact with fellow cowboys and bar patrons. Although this is limited for now, eventually, it could become like a video game version of the TV series Westworld, in which visitors pay to interact with incredibly lifelike robots in a Wild West theme park.AI also gives in-game opponents more “agency,” making them more reactive and challenging for players to defeat. This means smarter, more unpredictable enemies who provide a heightened level of achievement, novelty, and excitement for players.For example, AI Limit, released in early 2025, is an action RPG incorporating AI-driven combat mechanics. While drawing comparisons to Soulslike games, the developers emphasize its unique features, including the Sync Rate system, which adds depth to combat interactions.#2 AI-assisted matchmaking and player behavior predictionsAI-powered analytics can identify and predict player skill levels and playing styles, leading to more balanced and competitive matchmaking. A notable example is the implementation of advanced matchmaking systems in competitive games such as Apex Legends and Call of Duty: Modern Warfare III. These titles use AI algorithms to analyze not just skill levels but also playstyle preferences, weapon selections, and playing patterns to create matches optimized for player retention and satisfaction. The systems continuously learn from match outcomes to predict player behavior and create more balanced team compositions across different skill levels.By analyzing a player’s past performance, AI can also create smarter team formations. This makes for fairer and more rewarding multiplayer games, as players are matched with others who complement their skill and strategy.AI can monitor in-game interactions to detect and mitigate toxic behavior. This helps encourage positive social dynamics and foster a more collaborative and friendly online environment.#3 Personalized gaming experiencesMultiplayer games can use AI to analyze player behavior in real time, adjusting difficulty levels and suggesting tailored missions, providing rich experiences unique to each player. This creates personalized, player-centric gameplay that evolves dynamically and can change over time as a player’s knowledge and ability improve.Games like Minecraft and Skyrim already use AI to adjust difficulty and offer dynamic content, while Oasis represents a breakthrough as an AI-generated Minecraft-inspired world. The game uses generative AI to predict and render gameplay frames in real time, creating a uniquely responsive environment.Beyond world generation, modern games are also incorporating AI chatbots that give players real-time coaching and personalized skill development tips.How will AI continue to shape gaming?In the future, AI will continue to impact not just the player experience but also the creation of games. We anticipate AI revolutionizing game development in the following areas:Procedural content generation: AI will create vast, dynamic worlds or generate storylines, allowing for more expansive and diverse game worlds than are currently available.Game testing: AI will simulate millions of player interactions to help developers find bugs and improve gameplay.Art and sound design: AI tools will be used to a greater extent than at present to create game art, music, and voiceovers.How Gcore technology is powering AI gaming innovationIn terms of the technology behind the scenes, Gcore Everywhere Inference brings AI models closer to players by deploying them at the edge, significantly reducing latency for training and inference. This powers dynamic features like adaptive NPC behavior, personalized gameplay, and predictive matchmaking without sacrificing performance.Gcore technology differentiates itself with the following features:Supports all major frameworks, including PyTorch, TensorFlow, ONNX, and Hugging Face Transformers, making deploying your preferred model architecture easy.Offers multiple deployment modes, whether in the cloud, on-premise, or across our distributed edge network with 180+ global locations, allowing you to place inference wherever it delivers the best performance for your users.Delivers sub-50ms latency for inference workloads in most regions, even during peak gaming hours, thanks to our ultra-low-latency CDN and proximity to players.Scales horizontally, so studios can support millions of concurrent inferences for dynamic NPC behavior, matchmaking decisions, or in-game voice/chat moderation, without compromising gameplay speed.Keeps your models and training data private through confidential computing and data sovereignty controls, helping you meet compliance requirements across regions including Europe, LATAM, and MENA.With a low-latency infrastructure that supports popular AI frameworks, Gcore Everywhere Inference allows your studio to deploy custom models and deliver more immersive, responsive player experiences at scale. With our confidential computing solutions, you retain full control over your training assets—no data is shared, exposed, or compromised.Deliver next-gen gaming with Gcore AIAI continues to revolutionize industries, and gaming is no exception. The deployment of artificial intelligence can help make games even more exciting for players, as well as enabling developers to work smarter when creating new games.At Gcore, AI is our core and gaming is our foundation. AI is seamlessly integrated into all our solutions with one goal in mind: to help grow your business. As AI continues to evolve rapidly, we're committed to staying at the cutting edge and changing with the future. Contact us today to discover how Everywhere Inference can enhance your gaming offerings.Get a customized consultation about AI gaming deployment
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