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The packet.ai blog

Notes from the GPU frontier.

Deep dives on GPU infrastructure, model performance, and the economics of compute, from the team building software-defined GPUs at packet.ai.

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Announcement

Why We Raised $19M to Fix GPU Infrastructure

packet.ai raised $19M to build the scheduling layer that treats GPU compute as a multi-dimensional resource, not a reserved card. Here's what the round is for, who led it, and what we're building.

packet.ai TeamMarch 19, 2026

Latest

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Guide

How to Monetize Idle GPUs in 2026: A Provider's Guide

Your GPUs are either making money or burning CAPEX. In 2026, with AI demand outpacing supply, idle compute is the most expensive choice a data center owner can make.

packet.ai Team

October 1, 2026

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Guide

CI/CD for ML Pipelines: What's Different, and How SageMaker, Kubeflow, and Vertex AI Compare

Vertex AI Pipelines runs on the Kubeflow SDK, not a separate engine. Here is what actually changes when CI/CD meets machine learning.

packet.ai Team

September 30, 2026

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Guide

Migrating from Azure OpenAI Service to Token Factory: What Changes and What Doesn't

Azure OpenAI teams hit different migration friction: deployment names route to custom IDs, Entra ID tokens need full replacement, and the mandatory filter layer blocks prompts standard API users never see.

packet.ai Team

September 30, 2026

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Guide

Docker for GPU Workloads: The NVIDIA Container Toolkit, Explained

Half the Docker GPU guides online describe a deprecated, archived tool. Here is what is actually current, and the Compose syntax that trips people up.

packet.ai Team

September 30, 2026

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Guide

DeepSeek V4.1 Flash: The New Model, GPU Sizing, and API Guide

DeepSeek retired its old Flash model and reversed a plan to retire Pro too. Here is current pricing, plus which GPUs can actually run it.

packet.ai Team

September 28, 2026

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Announcement

packet.ai V2 Dashboard: A redesigned UI for users

Nine preinstalled apps, per-minute billing on screen before you commit, and a B200 provisioning in LA-2 while you are still reading the review panel. Here is the whole V2 flow, start to finish.

packet.ai Team

September 28, 2026

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Engineering

GB300 NVL72 vs GB200 NVL72: Is Blackwell Ultra Worth the Premium in 2026?

GB300 vs GB200 NVL72 looks like a 1.5x upgrade on paper. Benchmarks say 5% to 45%, and GB300 quietly cuts FP64 by 97%. If you are cost-sensitive, here is when the premium pays and when a B200 at $3.75/hr beats both.

packet.ai Team

September 28, 2026

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AI inference

Migrating from OpenAI to an OpenAI-Compatible Endpoint: What Actually Changes

The swap is smaller than you think, but three specific gotchas trip up most migrations. Here is what actually changes.

packet.ai Team

September 26, 2026

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Guide

RTX PRO 5000 Blackwell in the Cloud: 48GB vs 72GB, Pricing, and Where It Fits

NVIDIA quietly shipped a 72GB version of this card with zero fanfare. Here is what actually changed, and what it means for renting one.

packet.ai Team

September 25, 2026

Cover

AI inference

Claude API Pricing Compared: When an Open-Weight Alternative Actually Makes Sense

This is not a fair fight on every dimension. Here is where Claude wins, where an open-weight alternative wins, and what changed twice this month.

packet.ai Team

September 24, 2026

Cover

Technical

Open-Weight vs OpenAI API: GPT-5.6 Sol and GPT-6 Astra Cost Compared

GPT-5.6 Sol costs $4/$20 per million tokens on promo. GPT-6 Astra is $10/$50. Here is the exact volume where open-weight on GPU-hour billing wins, and where it does not.

packet.ai Team

September 23, 2026

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Technical

GB200 NVL72 Explained: When Is Rack-Scale Blackwell Worth It vs 8-GPU B200 Nodes?

Same Blackwell generation, radically different interconnect. Here is when a 72-GPU NVLink domain is actually worth it, and when 8-GPU B200 nodes are enough.

packet.ai Team

September 23, 2026

Cover

Technical

What Is a Token Factory? NVIDIA's AI Inference Framework Explained

Jensen Huang declared 2026 the year of inference at GTC. Token factories are what that actually looks like in hardware, and the economics behind them are changing how teams size GPU infrastructure.

packet.ai Team

September 22, 2026

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Technical

How to Build a RAG Pipeline: The Cost and Latency Mechanics

Retrieval does not just improve answers, it changes what every request costs. Here is the RAG cost and latency math most guides skip.

packet.ai Team

September 22, 2026

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Technical

Tool Calling in Self-Hosted LLMs: Function Calling Without OpenAI

A hosted API hides the parser-matching work. Here is what self-hosted tool calling actually requires, and where it can go quietly wrong.

packet.ai Team

September 21, 2026

Cover

Technical

Structured Output from LLMs: JSON Mode, Grammars and Constrained Decoding

Asking nicely for valid JSON is not a strategy. Here is how constrained decoding actually makes bad output impossible.

packet.ai Team

September 18, 2026

Cover

Technical

LLM Observability: Tracing, Token Metrics and Cost Attribution

A fluent response is not proof an LLM app is working. Here is how observability actually shows what happened, and what it cost.

packet.ai Team

September 17, 2026

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Technical

Batch Inference: Throughput Economics for Offline LLM Jobs

Not every request needs an answer right now. Here is how Batch API inference works, and why providers often price it at 50% of synchronous API rates.

packet.ai Team

September 16, 2026

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Technical

What Is GPU Cloud Computing? Explained for AI Engineers

Solo builders shouldn't pay AWS prices to fine-tune a 7B model. Here is what GPU cloud actually costs, which GPU you need, and how to go from signup to SSH-ready in under 5 minutes on packet.ai.

packet.ai Team

September 15, 2026

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Technical

LLM TCO Model: Build a Cost Calculator for Your Inference Stack

GPU rate is one line in the model, not the whole thing. Here is what a real LLM cost calculator needs, and why the numbers vary so much.

packet.ai Team

September 15, 2026

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Technical

Self-Hosting vs API: The Break-Even Point in Requests per Day

A rented GPU costs the same idle or busy. Here is the real formula for when self-hosting actually beats a managed API, and when it does not.

packet.ai Team

September 11, 2026

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Guide

Open-Weight vs Closed-Weight Models: The Definitive Guide (2026)

Every LLM deployment decision in 2026 starts with one question: open-weight or closed? For solo developers, the answer determines your cost structure and ops overhead. Here is what each path actually costs.

packet.ai Team

September 10, 2026

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Technical

Prompt Compression: Shrink Inputs While Preserving Quality

Compression itself has a cost too. Here is how prompt compression actually shrinks input tokens, and when the tradeoff genuinely pays off.

packet.ai Team

September 8, 2026

Cover

Technical

LLM API 429 Errors: Retry Logic, Backoff & Fallback

Your LLM API returns 429. Do you sleep(1) and retry? Add jitter? Cascade to a backup provider? Here is exactly what production-grade rate limit handling looks like, and when it is simpler to eliminate the limit entirely.

packet.ai Team

September 7, 2026

Cover

Technical

LLM Routing: Send Easy Queries to Cheap Models Automatically

Sending every query to the same model wastes money. Here is how LLM routing works, and the honest tradeoffs of using it.

packet.ai Team

September 4, 2026

Cover

Technical

Reasoning Models on GPUs: Why Thinking Tokens Can Inflate Your LLM Bill

A short answer does not mean a small generation cost. Here is how reasoning tokens work, and when the extra cost is actually worth it.

packet.ai Team

September 3, 2026

Cover

Technical

End-to-End Latency vs the Metrics That Make It Up

E2E latency is not one number to optimize. Here is what actually composes it, and how to diagnose which component is the real problem.

packet.ai Team

September 3, 2026

Cover

Technical

How LLM Response Streaming Works: SSE, TTFT, and UX

Streaming does not make a model faster. Here is how SSE actually works, why TTFT is a separate question, and what good streaming UX requires.

packet.ai Team

September 2, 2026

Cover

AI inference

Who Is Token Factory For?

Proprietary APIs bill you whether your app is sleeping or shipping. Self-hosting takes weeks to set up. Token Factory sits between the two. Here is who it is built for.

packet.ai Team

September 1, 2026

Cover

Technical

Prefill vs Decode: Disaggregated Inference Architecture Explained

Prefill is compute-bound, decode is memory-bound. Here is how disaggregated serving splits them across GPU pools, and when it actually pays off.

packet.ai Team

August 31, 2026

Cover

Technical

What Is an LLM API? Inference, Pricing, and Self-Hosting Explained

An LLM API exposes model inference. Here is what that means, how OpenAI-compatible and pricing actually work, and when a managed API beats self-hosting.

packet.ai Team

August 28, 2026

Cover

Technical

Context Window Cost: How Long Prompts Can 10x Your LLM Bill

A context window is a capacity limit, not a price. Here is how a growing conversation can cost far more than its final request size suggests.

packet.ai Team

August 27, 2026

Cover

Technical

Prompt Caching: How Much Can You Actually Save?

The headline discount is not your real savings figure. Here is how to calculate what prompt caching is actually worth for your traffic.

packet.ai Team

August 27, 2026

Cover

Technical

LLM Inference Cost by Model Size in 2026: 8B vs 70B vs 405B

Running a 70B model costs 10x more than an 8B at the hardware level. MoE models break that rule. Here is the VRAM math, GPU configs, and cost per million tokens for every tier on packet.ai.

packet.ai Team

August 27, 2026

Cover

Alternative

CoreWeave Alternatives for Startups: No Long-Term Contracts Required

CoreWeave H100 costs $6.16/GPU-hr in 8-GPU nodes with ~5-year contracts for best rates. packet.ai A100 is $1.43/hr per GPU with no contract. The best CoreWeave alternatives for AI startups in 2026.

packet.ai Team

August 26, 2026

Cover

Alternative

Hyperstack Alternatives in 2026: GPU Cloud Providers Compared

Hyperstack B200 costs $6.00/hr on-demand. packet.ai B200 is $3.75/hr - 37% cheaper on Blackwell. Compare the best Hyperstack alternatives on price, spot pricing, and global coverage in 2026.

packet.ai Team

August 26, 2026

Cover

Alternative

Nebius AI Alternatives in 2026: GPU Cloud Providers Compared

Nebius H100 on-demand costs $3.85/hr. packet.ai A100 80GB is $1.43/hr - a GPU Nebius does not offer. Compare the best Nebius AI alternatives on price, availability, and EU data residency in 2026.

packet.ai Team

August 26, 2026

Cover

Alternative

Paperspace Alternatives in 2026: Cheaper GPU Cloud for ML and AI Teams

Paperspace A100 now costs $3.18/hr on-demand. packet.ai A100 80GB is $1.43/hr - no subscription, no 36-month commitment. Here are the best cheap GPU cloud alternatives for ML and AI teams in 2026.

packet.ai Team

August 26, 2026

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AI inference

TTFT vs Tokens Per Second: Which LLM Performance Metric Matters for Your App?

A chatbot needs fast TTFT. A batch job needs high throughput. Here is how to tell which metric actually matters for what you are building.

packet.ai Team

August 26, 2026

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Guide

Top Neoclouds in India: GPU Infrastructure for Indian AI

India's neocloud market is forming fast. E2E Networks runs 2,048 H200s with H100 from Rs 249/hr and spot at 65-70% off. Cyfuture lists the cheapest domestic H100 at Rs 219/hr. NeevCloud is building 40,000 GPUs. Here is the full India GPU cloud picture for 2026.

packet.ai Team

August 25, 2026

Cover

AI inference

packet.ai Token Factory vs Groq vs Together AI: LLM API Pricing Compared

Groq is fastest. Together AI has the most models. packet.ai Token Factory has the lowest published rate for Llama 3.3 70B at $0.30/M. Here is how the three stack up across every scenario that matters.

packet.ai Team

August 25, 2026

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Alternative

Together AI Alternatives in 2026: Cheaper LLM Inference APIs Compared

Together AI charges $0.88/M for Llama 3.3 70B. Groq serves the same model at $0.59/M at 250 tokens/sec. DeepInfra at $0.23/M is the cheapest. Here is the full switching guide.

packet.ai Team

August 25, 2026

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Guide

Best GPU for Fine-Tuning LLMs in 2026: Llama, Qwen, and Mistral Benchmarked

The GPU that finishes a 70B QLoRA run cheapest is not the A100. It is the RTX 6000 Pro at $0.66/hr with 96GB VRAM. Here is the full GPU-by-model breakdown for Llama, Qwen, and Mistral.

packet.ai Team

August 25, 2026

Cover

Technical

What Is NVSwitch? Scaling GPU Communication Beyond 8 Cards

Running a 7B model? You don't need NVSwitch. Running 70B+ tensor-parallel? You do. Here is exactly where the line is, what the bandwidth gap costs you, and what to rent on packet.ai.

packet.ai Team

August 25, 2026

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Technical

How to Reduce LLM Inference Latency: 7 Proven Techniques (2026)

Most LLM latency problems trace back to a handful of causes. Here are seven proven techniques to fix them, and how to tell which one your problem actually needs.

packet.ai Team

August 25, 2026

Cover

Alternative

Vast.ai Alternatives: More Reliable GPU Cloud Options

Vast.ai hosts can reclaim your machine mid-run. Seven managed GPU cloud providers charge similar rates without the checkpoint roulette.

packet.ai Team

August 25, 2026

Cover

Alternative

Lambda Labs Alternatives: Better Pricing, Same Performance

Lambda raised H100 on-demand from $2.99 to $3.99/hr through 2025-2026, removed spot pricing entirely, and still sells out PCIe H100 instances during peak demand. Here are 7 alternatives worth running the math on.

packet.ai Team

August 24, 2026

Cover

Alternative

10 Best GPU Cloud Providers for AI in 2026

Specialized GPU clouds averaged 89% below hyperscaler H100 rates in August 2026. Here are the ten providers worth evaluating - ranked by what engineers actually care about: price, egress, setup time, and interconnect.

packet.ai Team

August 24, 2026

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Guide

What Is vLLM? The Open-Source LLM Inference Engine Explained

vLLM is a widely used open-source engine for self-hosted LLM inference. Here is what PagedAttention actually does, and why Hugging Face now recommends switching to it.

packet.ai Team

August 22, 2026

Cover

Alternative

RunPod Alternatives in 2026: GPU Clouds Worth Switching To

RunPod's Community Cloud has no SLA and logged 97.98% blended uptime over 18 months. If your workload has moved past fault-tolerant batch jobs, here are six providers worth evaluating - with real 2026 pricing for each.

packet.ai Team

August 21, 2026

Cover

AI inference

Speculative Decoding on Token Factory: 2-3x Faster LLM Inference Without the GPU Overhead

Token Factory runs EAGLE3 speculative decoding by default. Responses up to 3x faster, up to 96% cheaper than GPT-4o, with no GPU to manage.

packet.ai Team

August 21, 2026

Cover

Technical

Inference vs Training: What's the Difference and Why It Matters

Training builds a model once. Inference runs it forever after. Here is why that distinction changes everything about cost, hardware, and how to optimize each.

packet.ai Team

August 21, 2026

Cover

AI inference

Tokens vs Credits: How LLM API Billing Actually Works

Every LLM API bills by the token underneath. Credits are the wrapper on top. Here is how the two relate, and how to tell a trustworthy credit system from one that isn't.

packet.ai Team

August 20, 2026

Cover

Technical

DeepSeek V4 Flash API Pricing 2026: What It Actually Costs Now

DeepSeek raised API prices on August 16, 2026. Before you budget your next project, here's exactly what V4 Flash costs now — and where solo devs are finding better rates.

packet.ai Team

August 19, 2026

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Guide

Open-Source LLM API: Run Kimi K3, DeepSeek V4, Qwen3 Without Managing GPUs

DeepSeek, Kimi K3, and Qwen all ship OpenAI-compatible APIs. Here is what each actually costs right now, and when self-hosting beats paying per token.

packet.ai Team

August 19, 2026

Cover

Technical

GLM-5.3 API: Run Z.ai's MIT-Licensed Coding Model via OpenAI Endpoint

Z.ai shipped GLM-5.3 four days ago. It scores 66.9 on DeepSWE v1.1 and runs on an OpenAI-compatible endpoint you can point at with one line of code. Here is exactly how.

packet.ai Team

August 19, 2026

Cover

AI inference

What Is Time to First Token (TTFT)? LLM Latency Explained

TTFT is the wait before the first word appears, not how fast the rest streams. Here is what causes high TTFT and how it differs from tokens per second.

packet.ai Team

August 18, 2026

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AI inference

Kimi K3 API Guide: Run the World's Largest Open Model via Token Factory

Kimi K3 hit #1 on the open-source leaderboard July 2026. Here is what it actually costs to run it, the fastest way to call the API, and how solo devs can access it without a cluster.

packet.ai Team

August 18, 2026

Cover

Technical

What Is LLM Inference? A Beginner's Guide

Every time you message a chatbot, that is inference, not training. Here is what LLM inference actually means, how it works, and why it costs what it does.

packet.ai Team

August 17, 2026

Cover

AI inference

AI Token Cost: What Is a Token and What Does It Actually Cost in 2026

You are not charged per request. You are charged per token. Here is what an AI token actually is, why output tokens cost 4-10x more, and how to stop paying too much.

packet.ai Team

August 14, 2026

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Guide

What Is KV Cache? How LLM Inference Memory Works, and What Comes Next

KV cache is why your second token is fast. Here is how it actually works, why it eats GPU memory at scale, and new research on sharing it across models.

packet.ai Team

August 14, 2026

Cover

AI inference

Token Factory: packet.ai's OpenAI-Compatible LLM Inference API

Six open models. Cheaper than Together AI, Groq, and Fireworks on Llama 3.3 70B. $0.02 embeddings, $0.06 classification, $0.85 for DeepSeek-V3. Here is everything on Token Factory pricing and setup.

packet.ai Team

August 13, 2026

Cover

Guide

MiniMax M3 Self-Hosting Guide: GPU Requirements and Serving Setup

428B parameters, a license that is not Apache 2.0, and an 8-GPU documented deployment. Here is what MiniMax M3 actually needs before you deploy it commercially.

packet.ai Team

August 13, 2026

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Guide

Nemotron 3 Super Deployment: NVIDIA's Open Model on Your Own GPUs

Nemotron 3 Ultra grabbed the headlines. Super is the one you can actually self-host. Here is the real VRAM math and why its Mamba layers change everything.

packet.ai Team

August 12, 2026

Cover

Technical

FLUX vs SDXL: Image Generation API Costs, GPU Requirements, and the Cheapest Way to Run Both in 2026

DALL-E 3 charges $0.080 per image. Running FLUX.1 Dev on an L40S costs under $0.01 at scale. Here is the full cost math, GPU comparison, and a 10-minute setup guide.

packet.ai Team

August 11, 2026

Cover

Guide

Mixtral 8x22B GPU Requirements: The MoE Memory Math

39B active parameters does not mean 39B of VRAM. Here is the real memory math for Mixtral 8x22B, and why 8x7B is not a live recommendation anymore.

packet.ai Team

August 11, 2026

Cover

Technical

What Is NVfp4? Blackwell's 4-Bit Precision Format Explained

4 bits, twice the throughput: NVfp4 is what happens when NVIDIA bakes quantization into Blackwell Tensor Cores. Here is everything an ML engineer needs to know.

packet.ai Team

August 10, 2026

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Guide

Gemma 4 12B Deployment: Which Single GPU Actually Fits?

Google says 16GB. vLLM says 40GB. Both are right, for different questions. Here is what it actually takes to run Gemma 4 12B on a GPU in the cloud.

packet.ai Team

August 10, 2026

Cover

Technical

AWQ vs GPTQ vs FP8: LLM Quantization Methods Compared for Serving

AWQ protects the weights that matter before quantizing. GPTQ quantizes everything, then corrects the damage. FP8 skips the algorithm. Here is when each one wins.

packet.ai Team

August 7, 2026

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Technical

Speculative Decoding Explained: Draft Models and 2-3x Faster Inference

A small draft model guesses ahead, the big model checks its work in one pass. Here is why that is lossless, what makes it fast, and how to set it up in vLLM.

packet.ai Team

August 6, 2026

Cover

Technical

FP8 vs FP16 vs BF16: Precision Formats for AI Explained

Your 70B model needs 70 GB at FP8 versus 140 GB at BF16. That difference is one GPU or two. And on packet.ai, one B200 at $3.75/hr runs it cheaper than two H100s anywhere else.

packet.ai Team

August 5, 2026

Cover

Technical

vLLM Prefix Caching Explained: Reduce Latency for Repeated Prompts

Prefix caching is already on in your vLLM deployment. Here is what it actually does, how to tune it, and how to tell if it is earning its keep.

packet.ai Team

August 5, 2026

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Technical

NVLink vs PCIe for AI Workloads: When the Interconnect Is Your Bottleneck

Your model needs NVLink but your budget does not allow CoreWeave's 8-GPU minimum or AWS rates. This guide shows when PCIe works, when it does not, and how to access NVLink from $3.75/hr.

packet.ai Team

August 4, 2026

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Infrastructure

SXM vs PCIe GPUs: Form Factors, Power Limits and Real Performance Gaps

Same GPU silicon, two very different packages. Here is what SXM and PCIe actually require in power, cooling, and server hardware before you buy either.

packet.ai Team

August 3, 2026

Cover

Technical

Continuous Batching Explained: How Modern Servers Keep GPUs Full

Static batching makes every request wait for the slowest one. Here is the scheduling trick that fixed it, where it came from, and the tradeoff nobody mentions.

packet.ai Team

August 3, 2026

Cover

Technical

SGLang vs vLLM vs TensorRT-LLM: The 2026 Inference Engine Decision Guide

TGI is dead. SGLang beats vLLM by 29% on prefix-heavy workloads. TensorRT-LLM needs 28 minutes before its first request. Here is the decision framework that tells you which one to actually run.

packet.ai Team

July 31, 2026

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Technical

HBM3e vs HBM2e: Why Memory Bandwidth Decides LLM Throughput

Your GPU's TFLOPS rating does not decide how fast it generates tokens. Memory bandwidth does. Here's the spec that actually separates A100-era inference from H200-era inference.

packet.ai Team

July 31, 2026

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Guide

Qwen 3.6 VRAM Requirements: Both Models, One Consumer GPU

Two models, no cluster required. Here is exactly how much VRAM each Qwen 3.6 model needs, and why the MoE variant is not as light as its 3B active count suggests.

packet.ai Team

July 31, 2026

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Guide

GLM-5.2 Self-Hosting Guide: GPU Sizing for the Top Open-Weight Coder

GLM-5.2's 40B active parameters describe speed, not memory. Here's the real VRAM math Zhipu's own deployment recipe confirms, across every precision tier.

packet.ai Team

July 30, 2026

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Infrastructure

NVIDIA Blackwell Architecture Explained: What's New in the B200 and RTX 50 Series

Blackwell is the first NVIDIA GPU with a chiplet design. Two dies, one package, 10 TB/s between them. Here is what that actually changes for training, inference, and the cost of running large models.

packet.ai Team

July 29, 2026

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Technical

Not All GPU Hot Migration Is the Same

Every shared GPU platform claims 'seamless' migration. Here's what actually happens under the hood, and why vGPU migration and moving a live CUDA workload are not the same problem.

packet.ai Team

July 29, 2026

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Technical

What Is a GPU Cluster? Architecture, Networking and Scale Explained

Most teams rent a single GPU and call it a cluster. Real clusters have two layers of interconnect, three parallelism strategies, and one rule that breaks most training jobs: never cross the node boundary with tensor parallelism.

packet.ai Team

July 28, 2026

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Guide

Moonshot Kimi K3 GPU Requirements: Confirmed VRAM & Deployment Guide

Kimi K3 shipped less than a day ago, and hardware figures are still settling. Here's what's actually confirmed about VRAM and deployment, sourced directly from Moonshot's own repository.

packet.ai Team

July 28, 2026

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Infrastructure

Flux Image Generation on Cloud GPUs: VRAM Requirements, Speed and Cost Per Image (2026)

Flux.1 Dev in FP8 needs 18–23 GB VRAM and generates in 9–10 seconds on an RTX 4090 at $0.39/hr. Full VRAM table for Flux.1 Schnell, Dev, FLUX.2 [klein] 4B and 9B, and every precision level. Real cost per image at packet.ai rates.

packet.ai Team

July 27, 2026

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Guide

DeepSeek V4 Pro & Flash GPU Requirements: What They Actually Need

DeepSeek V4 Pro and Flash need very different hardware. Here's the real VRAM math for both, and why active parameters won't tell you what actually fits.

packet.ai Team

July 27, 2026

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AI inference

LLM Inference Cost in 2026: API Pricing and Cost per Million Tokens Compared

Your LLM API bill is not fixed. At 1B output tokens/month, Claude Sonnet 4.6 costs $15,000. Self-hosted Llama 4 70B on an H200 costs $130. Here is the math.

packet.ai Team

July 27, 2026

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Infrastructure

Fine-Tuning LLMs on GPU Cloud: A100 vs H100, QLoRA Memory Math and Cost Per Run

QLoRA fine-tuning a 70B model on a single A100 80GB costs $34–$51 and takes 24–36 hours. H100 at $2.50/hr cuts that to 8–12 hours and $20–$30. Here is the full cost math by method and model size.

packet.ai Team

July 24, 2026

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Guide

Multi-Node Training on GPU Clusters: When One Server Stops Being Enough

A single server's NVLink tops out at 8 GPUs. Here's what changes, technically and practically, once a training run needs InfiniBand-connected servers instead.

packet.ai Team

July 24, 2026

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Infrastructure

RTX 5090 for AI in the Cloud: Pricing, Benchmarks vs RTX 4090

32 GB GDDR7 at 1,792 GB/s, Blackwell architecture, from $0.59/hr on packet.ai. The RTX 5090 nearly doubles 30B inference throughput over the RTX 4090 and is the cheapest single GPU that fits 13B-22B models at FP16.

packet.ai Team

July 23, 2026

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Technical

vLLM Tutorial: How to Deploy and Serve LLMs on GPU Cloud (2026)

Most teams deploy vLLM and watch GPU utilisation sit at 30%. Here is what PagedAttention and continuous batching actually do to fix that, and how to run it on GPU cloud for a fraction of hyperscaler cost.

packet.ai Team

July 23, 2026

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Guide

Video Generation in the Cloud: GPU Requirements for LTX, Hunyuan & Wan

HunyuanVideo 1.5 needs a fraction of what the original HunyuanVideo requires, despite sharing the same name. Here's the real VRAM math for every major video model.

packet.ai Team

July 23, 2026

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Infrastructure

RTX 4090 for AI in the Cloud: Pricing, Performance and How It Compares to A100

24 GB GDDR6X, Ada Lovelace, from $0.39/hr on packet.ai. The RTX 4090 is the cheapest capable GPU for AI. Here is exactly what it runs, what it cannot, and when to upgrade.

packet.ai Team

July 22, 2026

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Guide

Langflow on a Cloud GPU: Size the Model, Not the Builder

Langflow barely needs a GPU at all. The model behind your flow is the real hardware decision, and here's how to size for both without touching your own machine.

packet.ai Team

July 22, 2026

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Infrastructure

GPU Cloud at 75% Less Than AWS: How packet.ai Prices Blackwell

AWS raised GPU prices again: $14.24/hr per B200, $6.88/hr per H100. Here is what the same NVIDIA silicon costs on packet.ai, and the math behind the gap.

packet.ai Team

July 22, 2026

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Guide

L40S GPU Cloud: Choosing the Right GPU for Production Inference

Most GPU comparisons start with the biggest card and work backward to justify it. L40S starts with what inference actually needs, and prices infrastructure accordingly.

packet.ai Team

July 21, 2026

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Guide

vLLM Docker Deployment: Best GPU for Production LLM Inference

Most teams hit OOM errors before their first successful vLLM request. Working Docker commands, exact VRAM math per model size, and GPU pricing from $0.66/hr.

packet.ai Team

July 20, 2026

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Guide

Running Llama 3 and Llama 4 in the Cloud: GPU Sizing From 8B to 405B

17B active parameters sounds small enough for any GPU. It isn't the number that actually decides your hardware. Here's the real VRAM math for every Llama model, 8B to 405B.

packet.ai Team

July 20, 2026

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Technical

Bare Metal vs VM GPU Performance: What the Benchmarks Actually Show

Bare metal vs virtual machine GPU performance: the benchmark numbers cloud providers quote are single-workload, ideal-condition results. Here is what the data actually shows across inference, training, and multi-node distributed workloads.

packet.ai Team

July 19, 2026

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Technical

The Noisy Neighbor Problem on GPU Cloud: p99 Latency, Throughput Variance, and How to Avoid It

Noisy neighbor problem on GPU cloud: why your p99 doubles when a co-located tenant saturates the PCIe fabric, and the four checks that prove it.

packet.ai Team

July 18, 2026

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Infrastructure

NVIDIA A100 vs H100 in 2026: Price, Performance and Which GPU Fits Your Workload

The A100 is $1.43/hr. The H100 is $2.50/hr and delivers 2.88x more LLM inference throughput at high concurrency. For QLoRA fine-tuning, total run cost is within 12.6% at 70B. Here is the full benchmark and cost breakdown.

packet.ai Team

July 17, 2026

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September 10, 2026

Open-Weight vs Closed-Weight Models: The Definitive Guide (2026)

Every LLM deployment decision in 2026 starts with one question: open-weight or closed? For solo developers, the answer determines your cost structure and ops overhead. Here is what each path actually costs.

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Prompt Compression: Shrink Inputs While Preserving Quality

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LLM API 429 Errors: Retry Logic, Backoff & Fallback

Your LLM API returns 429. Do you sleep(1) and retry? Add jitter? Cascade to a backup provider? Here is exactly what production-grade rate limit handling looks like, and when it is simpler to eliminate the limit entirely.

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September 4, 2026

LLM Routing: Send Easy Queries to Cheap Models Automatically

Sending every query to the same model wastes money. Here is how LLM routing works, and the honest tradeoffs of using it.

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September 3, 2026

Reasoning Models on GPUs: Why Thinking Tokens Can Inflate Your LLM Bill

A short answer does not mean a small generation cost. Here is how reasoning tokens work, and when the extra cost is actually worth it.

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