Author
Eli Mogul
Content Writer & Editor
Eli is the content writer and editor at Telnyx. Born and raised in Chicago, Eli attended the University of Missouri where he obtained a BA in Journalism. Eli joined Telnyx in August of 2025. In his spare time, you'll find Eli reading, playing video games, or running.
- 60
- Articles
- 2023
- Joined
Latest articles
Page 1 of 2 · 60 articles, most recent first.
WirelessIoT hacking: how devices get breached and how to stop it
IoT hacking usually starts with a public IP and a default password. See how attackers take over connected devices and how to lock down a cellular fleet.
InferenceInference cost explained: why your AI bill rises as prices fall
Token prices fell 280-fold, yet AI bills keep rising. Learn what drives inference cost and five steps to cut it by up to 75%.
TelnyxInference benchmarks: which numbers predict latency on your traffic
Inference benchmarks only predict your latency when they match your traffic. Learn which metric fits your workload, then run your own tail-latency check in an afternoon.
NetworkingAI data residency vs sovereign AI: what to check in vendors
AI data residency is more than where files sit. See what to ask vendors about transcripts, inference, and logs before you buy.
InferenceOpen weight models: what they are and how to use them
Learn how open weight models differ from open source, which lead in 2026, and how to run them on your terms.
InferenceTop AI inference platforms: how to evaluate providers on real cost
Six checks to predict your inference bill and latency, plus how the top AI inference platforms compare on pricing.
TelnyxLLM inference explained: phases, bottlenecks and the fastest setup
How LLM inference works, which optimizations fix slow replies, and why the distance between your users and the GPU decides latency.
InferenceInference as a service: how it works and what it costs
Inference as a service wraps that serving layer in a managed product. Rather than standing up an inference engine, provisioning GPUs...
InferenceAI inference hardware: How to choose chips and placement
Rank inference chips by bandwidth and VRAM per dollar, then decide what to own, rent, or run on GPUs in your users’ region.
InferenceInference optimization: cut LLM latency and cost
Learn which inference optimization techniques cut LLM latency and cost per token, from quantization and KV cache paging to continuous batching.
InferenceReal-time voice inference: where every millisecond goes on a live call
Real-time voice inference starts at the carrier. Trace every hop in a caller’s wait and find the one to cut first.
InferenceEdge inference: where to run AI models for low latency
Where your model runs sets how fast your agent can answer. Compare device, on-prem, network edge, and cloud inference for real-time AI.
InferenceOpen Source vs Frontier Models: Which Should Your Agents Run On?
GLM-5.3 output costs $4.00 per million tokens. GPT-6 Astra costs $50.00. Here's where open-weight models already match frontier models for agents, where closed models still win, and how to route between them.
Insights and ResourcesB300 GPU rental price per hour in 2026: what you actually pay
B300 GPU rental costs $7.10 to $17.80 per hour in 2026. Here's what each provider charges and when paying per token beats renting.
TelnyxHGX B300 cluster sizing: the node, network and control plane numbers
Every number you need to size an HGX B300 cluster, from 288 GB GPUs to control plane nodes, plus why vendor spec sheets disagree on the same board.
InferenceNVIDIA B300 pricing in 2026: per hour, per system and per token
B300 pricing runs $7.10 to $17.80 per GPU hour. Here's when the extra memory pays off, and when per-token pricing costs less.
InferenceInference Infrastructure: What to Run Where and Why It Matters
Hosted API, hyperscaler GPUs, or bare metal? Compare the three ways to run AI inference, see where latency comes from, and pay for speed only where it earns revenue.
VoiceVoice AI Agents Compared on Latency: 2026 Benchmarks
Telnyx had the lowest median latency of five voice AI platforms in a caller-side test over real phone calls. Here's how six platforms compare across four third-party benchmarks.
InferenceWhat is an inference engine? Types, uses, and vLLM
An inference engine is the software component of an AI system that applies logical rules or trained models to data to produce conclusions, decisions, or predictions. Learn how they work and where they are used.
VoiceVoIP infrastructure explained: find the layer behind every bad call
Bad call quality starts in one of seven VoIP infrastructure layers. See what each one does and where calls break.
Insights and ResourcesModel serving: how to run open-weight LLMs close to your users
Model serving keeps a trained model on GPUs and answers requests through an API. Learn the three layers of LLM serving and how to run open-weight models in-reg...
InferencevLLM inference: how it works and when to stop self-hosting
Run vLLM inference on one GPU, tune the config flags that matter, and see when moving the same client to a managed endpoint costs less.
Edge ComputeEdge computing applications: 12 real use cases and latency budgets
Real edge computing applications, what they solve, and how teams deploy edge architectures in production.
InferenceThe best open source LLMs in 2026 for coding, agents, and voice
Last updated: September 28, 2026. Open model versions change monthly, so every pick below carries a release date and states whether its benchmark score is vendor-reported or independently measured.
Conversational AIInference latency: where milliseconds go and how to cut them
Inference latency is a systems problem, not just a model problem. The model is one of three layers, and for real-time AI it is rarely the layer with the most latency to give back.
InferenceHow machine learning inference works, from forward pass to live call
The inference process in machine learning is the production stage where a trained model takes new inputs and produces predictions.
Guides and TutorialsSynthetic speech detection: Why infrastructure ownership decides who wins
Practical synthetic speech detection for real world voice: What works, what breaks, and how to deploy it.
InferenceTPU vs GPU Compared for AI Training and Inference
This guide covers the architecture behind each chip, verified benchmark and migration data, framework ecosystems...
Insights and ResourcesStateful Edge Functions
Stateful edge functions give edge compute persistent state without database round trips. Learn what they are, how they work, and why SQL at the edge matters.
TelnyxThe 6 Best SMS Marketing Platforms in 2026
The 6 best SMS marketing platforms compared by API access, pricing, compliance tools, and deliverability. Find the right platform for your business.
SIP TrunkingSIP trunking cost: what you actually pay by pricing model
This guide breaks down the two dominant SIP trunking pricing models...
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Insights and ResourcesHow to use a serverless SQL database for edge functions
A serverless SQL database for edge functions scales to zero, speaks HTTP, and places data near the function runtime. Learn how it works, compare providers, and set up Telnyx SQL Database with TypeScript.
Edge ComputeDevOps Automation Tools for AI Agents
DevOps automation tools for AI voice agents cover six stages. See what a multi-vendor stack adds and where an integrated platform reduces the work.
Guides and TutorialsWhat is a fine-tuning API, and where should the weights actually run?
This guide defines the term, walks through the parameter-efficient methods that made fine-tuning affordable, covers the safety guardrails the research community now considers mandatory...
VoiceConversational AI vs. Generative AI
Compare conversational AI and generative AI by purpose, intent, and use cases. Learn the key differences and how they complement each other.
WirelessWhat is a machine-to-machine (M2M) SIM card?
Machine-to-machine (M2M) SIM cards are the key to innovation, optimization, and enhanced IoT security. Keep reading to learn why.
IoTWhat is IMSI switching, and how does it work?
IMSI switching allows devices to natively connect to multiple different networks across the globe. Learn about IMSI switching, its benefits, and use cases.
Conversational AIE-commerce and contact centers: Selling digitally
Learn how an e-commerce contact center with the right tools can boost customer satisfaction and sales.
Conversational AIWhat is distributed inference?
Distributed inference is the practice of running model inference across multiple machines or geographic regions rather than a single server.
NetworkingWhat is inference engineering and why it matters
Inference engineering optimizes how a model serves predictions, not what the model says.
Insights and ResourcesCall Sentiment Analysis How It Works and Why It Matters
Learn how call sentiment analysis works, the customer insight use cases it unlocks, and the tools and providers that turn every call into action.
IoTICCID number: find, decode, and use it
Discover how SIM card ICCID numbers enable tracking and provisioning for IoT deployments and mobile fleets.
Conversational AIGoogle voice verification: why voice beats SMS
SMS works for most verification flows. But when carrier filtering or VoIP restrictions block delivery, voice calls provide a reliable fallback.
Insights and ResourcesWhat are edge functions and how they work
Edge functions run server-side code at data centers close to your users. Learn how they work, how they compare to serverless, and how to choose the right edge platform.
TelnyxAI Dev Ops: Practical guide to automate IT operations
Learn how AI Ops cuts alert noise, automates root cause analysis and remediation, and keeps large-scale voice and AI agent operations reliable, high-quality, and cost-efficient.
Networking5 Cloudflare D1 alternatives for edge SQL workloads in 2026
Cloudflare D1 caps each database at 10 GB and processes queries one at a time, which is fine until it isn't. Here are five serverless SQL alternatives, what each one actually fixes, and how to migrate off D1 without rewriting your queries.
SIP TrunkingTop 5 telephony trends in 2026
Telephony and connectivity solutions are poised to change and grow. Here we’ll guide you on what to watch for in 2026.
Conversational AIWhat is model deployment in machine learning
Model deployment is the process of moving a trained machine learning model from a development environment...
InferenceWhat are frontier models and why data sovereignty matters
This guide explains what frontier models are, why data sovereignty has become the real buying question, and how Telnyx runs frontier-grade models like GLM-5.2 on GPUs it owns, with no conversation monitoring.
InferenceWhat is an open-source LLM? Definition and applications
Learn how using open-source LLMs can improve your apps by making them smarter, more flexible, and better suited to your needs.
