Ai Rigs — 202 Articles on SpecPicks

All SpecPicks articles in the Ai Rigs category — benchmarks, buying guides, and in-depth hardware analysis. Browse the full archive →

• RTX 3090 vs RTX 4090 for LLM Inference: Same 24GB (2026) — LocalScore puts the RTX 4090 at 78.0 tok/s on a 14B model and the RTX 3090 at 55.8 — same 24GB, 1.4x the speed, 2.2x the price. 2026-09-03 · 9 min read
• RTX 3060 12GB vs RTX 3090 for Local LLMs (2026) — An RTX 3090 runs Llama 3.1 8B at 95.7 tok/s against 52.2 for an RTX 3060 12GB — but VRAM, not speed, decides this one. 2026-09-03 · 9 min read
• RTX 3060 12GB for Local LLMs: The Complete 2026 Guide — Median tok/s by model size from 49 published RTX 3060 12GB runs, the point where 12 GB stops being enough, and the full cluster index. 2026-08-27 · 9 min read
• Local LLM Setup in 2026: AMD GPU Guide by Model Size — A synthesis of AMD GPU options for running local LLMs in 2026 — VRAM needs by model size, RX 7900 XTX vs Instinct MI210/MI300X, and the… 2026-08-08
• Why Privacy-Preserving AI Demand Is Rising in the LLM Era — Enterprise adoption of large language models is reshaping demand for privacy-preserving AI infrastructure, from encrypted memory to local… 2026-08-08
• Running Qwen3.5/3.6 with NextN MTP on an RTX 3090 Ti — How NextN multi-token prediction speculative decoding works in llama.cpp, and what a single RTX 3090 Ti can realistically run locally with… 2026-08-08
• Optimizing LTX-2.3 Inference Speed on an RTX 3080 Ti — How TensorRT, FP16 precision, and smarter batching cut LTX-2.3 video-diffusion inference time on a 12GB RTX 3080 Ti — with sourced caveats… 2026-08-07
• Local LLM Autocomplete + Agentic Coding on 16GB VRAM — A synthesis of public documentation and community reports on running local LLM autocomplete and agentic coding on a single 16GB GPU with… 2026-08-07
• Open Source AI Code Reviewers You Can Self-Host in 2025 — Real open-source AI code reviewers you can self-host today: PR-Agent (Qodo Merge), Aider, and Continue, plus the hardware they actually… 2026-08-07
• Qwen-Image vs ERNIE vs FLUX.2 Dev: RTX 5090 Style Test — A synthesis of public model cards and community tests comparing Qwen-Image, ERNIE, and FLUX.2 Dev across eight art styles on a single RTX… 2026-08-07
• How to Backup a NAS on a Budget in 2026 — A budget NAS backup plan using free rsync/Duplicity tools, cron scheduling, and inexpensive external drives instead of a cloud subscription. 2026-08-07
• The Pac-Man Benchmark: Testing Local Agentic Coding AI — The 'Pac-Man benchmark' — cloning the arcade classic in one AI prompt — has become an informal gut-check for local coding agents. Here's… 2026-08-07
• Local LLMs for Generating Interactive Textbooks On the Fly — Local LLMs can draft adaptive, recursive textbook chapters on-device — no cloud API needed. Here's the hardware, software, and real limits… 2026-08-06
• Qwen 0.8B AI Detectors: Fine-Tuned on Pangram-Style Data — Small fine-tuned models like a Qwen 0.8B AI content detector promise fast, local text detection. Here's what's verifiable and what to… 2026-08-06
• Pushing a 6GB VRAM Laptop to Its Limits With Qwen3.6-35B-A3B — Can a 2021-era 6GB VRAM laptop run the Qwen3.6-35B-A3B MoE model? A synthesis of quantization, CPU offload, and where aging hardware hits… 2026-08-06
• 18 LLMs Benchmarked on OCR: Why Cheaper Models Often Win — An open-sourced OCR benchmark spanning 18 LLMs and 7,000+ calls finds older, cheaper models often match flagship accuracy at a fraction of… 2026-08-06
• Field Report: Running Qwen 3.6 35B-A3B on a 32GB M2 Mac — What it takes to run Qwen 3.6 35B-A3B's MoE coding model on a 32GB M2 MacBook Pro: memory math, quantization tradeoffs, and realistic… 2026-08-06
• Can Local LLMs Actually Do Anything Useful? — A synthesis of public benchmarks and community reports on what local LLMs are genuinely good at today, and where cloud APIs still hold an… 2026-08-06
• Is vLLM Worth It If You're Not Serving Other Users? — vLLM's speedups come from batching concurrent requests. For solo local-AI use, community consensus favors llama.cpp instead. 2026-08-06
• What Happened to the LLM Training Data Shortage? — The 2023 fear that AI labs would run out of human text didn't play out as predicted. Synthetic data and reasoning models changed the math… 2026-08-05
• Qwen3.6 the Right Way: Run It Through a Pi Coding Agent — How to actually pair Qwen3.6 with a Raspberry Pi coding agent: which AMD GPU should host the model, and why Pi-based GPU passthrough… 2026-08-05
• Train a Kick Drum AI Model on 6GB VRAM (Linux Guide) — How to train a generative kick drum model on a budget Linux desktop with only 6GB VRAM, per ROCm and PyTorch documentation and public… 2026-08-05
• RTX 5090 vs. M5 Max 128GB for Agentic Dev (2026) — RTX 5090 or Apple's M5 Max with 128GB unified memory for agentic coding? A synthesis of specs, memory tradeoffs, and cost for AI dev… 2026-08-05
• Run Chrome's Tiny Gemini Nano AI on PC Without a GPU — Chrome's built-in Gemini Nano model officially requires a GPU. Here's what the requirement actually gates, and what CPU-only workarounds… 2026-08-04
• ProgramBench: Can LLMs Rebuild Programs From Scratch? — ProgramBench asks LLMs to rebuild real software from binaries and docs. Here's what the evidence shows, and the GPU VRAM it takes to run… 2026-08-04
• Have Qwen Said Anything About Further Qwen 3.6 Models? — No confirmed Qwen roadmap ties Qwen 3.6 to 9B/122B/397B AMD Instinct tiers — the claim's own hardware specs don't match AMD's published… 2026-08-04
• $400 Qwen 3.6-27B Setup: Is the Dual RTX 3060 Claim Real? — A $400 dual RTX 3060 12GB build claims 30-50 t/s on Qwen 3.6-27B. Here is what the VRAM math and multi-GPU bandwidth limits actually… 2026-08-04
• Dual GPU Llama.cpp Speedup: What Actually Helps — Does a second GPU actually speed up llama.cpp, or mainly add VRAM? A synthesis of split-mode behavior, ROCm vs CUDA, and real dual-GPU… 2026-08-03
• GPU VRAM Guide: Running a 5GB TTS Model Locally — A synthesis of GPU specs and community reports on running small TTS models with a 5GB VRAM footprint, from budget cards to 12GB… 2026-08-03
• Running a 26B LLM Locally With No GPU: The CPU Setup Guide — A 26B-parameter model can run on CPU alone if RAM and quantization are matched—here's the memory math, format choice, and realistic speed… 2026-07-31
• Training an LLM in Swift, Part 1: Matrix Mult Speed — How Swift's Accelerate, SIMD, and Metal stack take matrix multiplication from naive Gflop/s loops to Tflop/s-class LLM training throughput. 2026-07-31
• GitHub Copilot vs Claude Code vs OpenCode Benchmark 2026 — Community tests pit GitHub Copilot, Claude Code, OpenCode and Pi against the same open model. Here's what a same-model harness test can… 2026-07-30
• Train Your Own LLM From Scratch: 2026 Hardware Guide — A synthesis of public GPU specs, frameworks, and cost reporting on what it actually takes to train an LLM from scratch versus fine-tuning… 2026-07-29
• Gemini Intelligence Hardware Requirements Explained — Cloud Gemini runs entirely server-side, needing no GPU. Gemini Nano's on-device Chrome and Pixel features have real VRAM and storage… 2026-07-28
• 48GB vs 64GB DDR5 for Gaming and AI: Worth It? — 48GB and 64GB DDR5 kits rarely boost gaming FPS, but they matter for AI inference, multitasking, and content creation. Here's when the… 2026-07-28
• Qwen3.6-35B-A3B VRAM Optimization: Why Bigger Quants Win — Qwen3.6-35B-A3B's mixture-of-experts routing makes low-bit quantization riskier than usual — on 8GB and 12GB GPUs, a bigger GGUF quant can… 2026-07-28
• 42 LLMs Tested for Apocalypse Compliance: What Data Shows — A viral claim that 42 LLMs failed apocalypse-scenario safety tests oversimplifies what real AI benchmarks like HarmBench actually measure… 2026-07-28
• Local AI News You Missed in April 2026 — Editorial synthesis of April 2026's local AI landscape: notable open-weight releases, realistic hardware requirements, and shifts beyond… 2026-07-28
• Self-Hosted Personal Finance: n8n + Actual Budget + Claude — How n8n, Actual Budget, SimpleFIN, and the Claude API combine into a self-hosted personal finance automation stack — no cloud budgeting… 2026-07-28
• Qwen3.6-27B at 80 TPS on RTX 5090: Is the Claim Real? — A viral claim puts Qwen3.6-27B at 80 tok/s with 218k context on one RTX 5090 via vLLM 0.19. Here's what the hardware math actually supports. 2026-07-28
• Qwen MTP on LLaMA.cpp + TurboQuant: What's Actually Verified — MTP is a real speculative-decoding technique from DeepSeek-V3, but claims about a Qwen+llama.cpp "TurboQuant" release lack a citable… 2026-07-28
• Qwen3.6-27B at 72 Tok/s on RTX 3090: What's Real — The viral '72 tok/s' claim for Qwen3.6-27B on an RTX 3090 lacks a verifiable source. Here's what vLLM on Windows actually supports today… 2026-07-27
• Why LLM Reasoning Still Happens in Words, Not Vectors — LLMs reason in text, not vectors, because token-based chain-of-thought keeps outputs interpretable, auditable, and compatible with today's… 2026-07-27
• Local LLM Image Generators: Best AMD GPUs in 2025 — A synthesis of public specs and community reports on running Stable Diffusion XL and Kandinsky locally on AMD Instinct and Radeon Pro… 2026-07-27
• Local LLM Hardware in 2025: Picking GPUs, CPUs & RAM — A synthesis of public specs and community reports on GPUs, CPUs, RAM, and storage for running local LLMs in 2025 — AMD, NVIDIA, and Intel… 2026-07-26
• Local LLM Benchmarks 2025: AMD Instinct vs Radeon Pro — AMD's Instinct MI300X, MI350X/MI355X, and Radeon PRO W7900 compared for local LLM hosting: memory capacity, bandwidth, and where each fits… 2026-07-26
• AI Rigging 3D Models: The 2026 Hardware Guide — What GPU, RAM, and storage actually matter for AI-assisted 3D rigging in Blender and Maya, per public specs and vendor documentation. 2026-07-26
• RTX 5090 AI Models: Performance, VRAM, Power — The RTX 5090's 32GB of VRAM and 1.8TB/s bandwidth reshape which AI models fit locally. Here's what public specs and benchmarks actually… 2026-07-26
• Dual RTX 3090 LLM Training: 2026 Benchmarks & Build Guide — Dual RTX 3090 rigs pool 48GB of VRAM for local LLM training and inference. See real specs, PSU/cooling needs, and costs versus a single… 2026-07-25
• Ollama vs LM Studio vs vLLM: Choosing a Local LLM Runner — Ollama, LM Studio, and vLLM take different approaches to local LLM inference. This synthesis compares architecture, GPU support, and… 2026-07-25
• Anthropic's 2GW AMD Deal: Should You Still Run Local? — A 2GW hyperscaler buildout means tighter cloud rate limits, not cheaper API tokens. Here's the local RTX 3060 12GB build that breaks even… 2026-07-23 · 9 min read
• Flux 3 Native-Audio Video: Can a 12GB GPU Run It? — Flux 3 needs 16-18GB at fp16, but a q4 or q5 quantized build runs on a 12GB RTX 3060 with CPU offload. Here's the setup that actually works. 2026-07-23 · 9 min read
• Coral TPU for LLM Inference: What the Specs Really Say — Google's own Edge TPU specs and community reports show the Coral accelerator is built for vision models, not large language models—here's… 2026-07-21
• 2025 Local LLM Leaderboard: Best AMD GPUs Ranked — A synthesis of public specs and community reports ranking AMD's Instinct and Radeon GPUs for running local LLMs in 2025. 2026-07-21
• Best GPU for LLM Training and Inference in 2026 — Public specs and community benchmarks point to data-center HBM cards for LLM training and 24GB consumer GPUs for local inference — here's… 2026-07-21
• Strix Halo LLM Benchmarks: What AMD's APU Delivers — AMD's Strix Halo APU targets local LLM inference with unified memory up to 128GB. Here's what public benchmarks and community reports… 2026-07-20
• Ryzen AI Max LLM Test: What the Public Data Shows — Public specs and community measurements on Ryzen AI Max's unified memory reveal what it actually enables for local LLM inference — and… 2026-07-20
• Ryzen AI Max+ 395 LLM Performance: What to Expect — A synthesis of AMD's published specs and community reports on how the Ryzen AI Max+ 395's unified memory shapes local LLM inference in 2025. 2026-07-20
• Ryzen AI Max for Local LLMs: What the Hardware Enables — AMD's Ryzen AI Max pairs a Zen 5 CPU with up to 128GB of unified memory, changing which local LLMs fit at all versus a discrete-GPU… 2026-07-20
• AMD Ryzen AI Max for Local LLMs: What the Specs Mean — AMD's Ryzen AI Max APUs use unified memory to run large local LLMs without a discrete GPU. Here's what that means for real-world inference. 2026-07-19
• Ryzen AI Max+ 395 LLM Inference: Specs, Bandwidth, Reality — AMD's Ryzen AI Max+ 395 pairs 16 Zen 5 cores with up to 128GB of unified memory. Here's what its specs mean for running local LLMs, per… 2026-07-19
• Unified RAM for LLMs: 2025-2026 Hardware Guide — How unified memory architecture from Apple Silicon and AMD's Ryzen AI Max changes local LLM hardware choices in 2025-2026, and how it… 2026-07-19
• Mac Unified Memory for LLMs: What Matters in 2026 — How Apple's unified memory architecture changes local LLM inference on Mac, and where it still loses to HBM-equipped datacenter GPUs. 2026-07-19
• Local AI Image Generation: Best AMD GPUs for 2026 — AMD's ROCm software stack now runs Stable Diffusion and ComfyUI locally on Radeon hardware — here's how the RX 7900 XTX and W7900 actually… 2026-07-19
• Local LLM Agent Infrastructure: 2026 Hardware Guide — What hardware local LLM agent infrastructure actually needs in 2026 — from budget consumer GPUs to workstation and datacenter cards, per… 2026-07-19
• Local LLM on Mac: The 2026 Setup Guide — A synthesis of public tooling docs and community benchmarks on running local LLMs on Apple Silicon Macs — hardware picks, quantization… 2026-07-18
• Local AI Server LLM Setups 2025: What Hardware Matters — A synthesis of public specs and community builds on what actually matters for a local AI server running LLMs in 2025 — memory, GPU tier… 2026-07-17
• Local LLM in VSCode: The 2026 Setup Guide — How to run a local LLM inside VSCode in 2026 — the extensions, Ollama setup, model picks, and hardware tiers that actually matter for… 2026-07-17
• Intel Arc B580 for LLM Inference: What It Can Actually Do — Intel Arc B580's 12GB VRAM and IPEX-LLM/llama.cpp support make it a budget option for local LLM inference — not a datacenter training card. 2026-07-17
• IPEX-LLM Ollama Update 2026: What's New for Intel GPU Rigs — The latest IPEX-LLM release refines Ollama's Intel GPU backend, widening Arc and Data Center GPU Max support and clarifying quantization… 2026-07-17
• Thinking Machines Drops Inkling, a 975B Open Model Leading US Labs — Thinking Machines' Inkling is a 975B MoE, open weights, tops the intelligence index. What it takes to self-host it, and what to run on a… 2026-07-16 · 10 min read
• vLLM 0.21 Adds Intel GPU Support: What It Means for Budget AI Rigs — vLLM 0.21 XPU turns a budget Arc rig into a 15-user shared inference host. Here is what changed, how it stacks against Ollama, and who… 2026-07-16 · 10 min read
• Intel Arc B580 vs RTX 3060 12GB for Local LLMs in 2026 — Arc B580 wins raw bandwidth and price. RTX 3060 12GB wins software maturity and CUDA. Real tok/s numbers, per-quant breakdown, and a… 2026-07-16 · 10 min read
• Can You Run Kimi K3 Locally? VRAM Math for the New Open Model — Kimi K3 needs ~500GB VRAM at q4 for real throughput. Here is what a 12GB RTX 3060 can actually do with it, and where the API wins outright. 2026-07-16 · 11 min read
• Beyond LLMs: How Agent Logic Scales Enterprise AI — Agent logic—task decomposition, tool routing, and state persistence—solves the cost and reliability gaps that stall enterprise LLM… 2026-07-14
• Local Video-Gen on 12GB: What an RTX 3060 Does in the Gemini Omni Flash Era — Local text-to-video on a 12GB RTX 3060 is real in 2026, but slow: expect 60-180 seconds per 4-second clip at 512p. Full quant matrix, CPU… 2026-07-14 · 8 min read
• Run Soofi S 30B Locally: What a 12GB RTX 3060 Can Actually Do — A 12GB RTX 3060 can run Soofi S 30B, but only with q3 quantization and CPU offload. Expect 4-8 tok/s and plan for a fast NVMe. Full… 2026-07-14 · 9 min read
• Best Mac for AI & LLM Workloads in 2026 — Apple Silicon's unified memory architecture makes Macs uniquely capable for local LLM inference. Here's how to choose the right Mac for… 2026-07-14
• Mac Studio AI Model 2025: Performance vs AMD Alternatives — Apple Silicon unified memory vs AMD discrete GPUs for local LLM inference and Stable Diffusion — a synthesis of public benchmarks and… 2026-07-14
• Ryzen AI Max+ 395 (Strix Halo) Mini PC vs RTX 3060 12GB for Local LLMs — Strix Halo's huge unified LPDDR5X pool fits 70B models; the RTX 3060 12GB wins on tok/s for 8-13B. Real specs, benchmarks and verdict. 2026-07-13 · 20 min read
• Ollama vs LM Studio vs GPT4All on a 12GB GPU (2026) — Ollama, LM Studio and GPT4All on the same 12GB RTX 3060: feature deltas, tok/s at Q4, VRAM headroom, and which local runner to install… 2026-07-13 · 16 min read
• Intel Arc LLM Performance: A770, B580 & Pro B60 Guide 2025 — Public benchmarks and community data on Intel Arc A770, B580, and Pro B60 for local LLM inference — VRAM limits, SYCL setup, model… 2026-07-13
• Intel Arc LLM Inference: A770 & B580 Guide 2025 — Public benchmarks and community data on running local LLMs with Intel Arc A770 and B580 — VRAM fit, software stack, and cost vs NVIDIA and… 2026-07-13
• Intel Arc LLM Support: What Works in 2026 — Intel Arc GPUs support local LLM inference via llama.cpp SYCL, OpenVINO, and IPEX. Here's what works, what doesn't, and which Arc GPU fits… 2026-07-13
• Intel Arc B580 LLM Inference: 12GB Battlemage Benchmarks — Public benchmarks and community reports show how Intel's Arc B580 handles 7B–13B LLM inference via OpenVINO and llama.cpp SYCL on 12GB… 2026-07-13
• Arc A770 vs B580 for Local LLM Inference: 2025 Comparison — Intel Arc A770's 16 GB VRAM edges out B580's 12 GB for large-model LLM inference; B580's newer Xe2 architecture and lower entry price suit… 2026-07-13
• Intel Arc A770 LLM Performance: Local Inference Guide — Intel Arc A770's 16GB GDDR6 gives it unusual VRAM depth for a budget GPU. Here's what community benchmarks and Intel's own tooling show… 2026-07-13
• Intel Arc A770 for Local LLMs: 2026 Benchmark Guide — The Intel Arc A770 16GB offers more VRAM than many RTX 4060 builds at a competitive price — here's what community benchmarks reveal about… 2026-07-13
• Intel Arc A770 16GB for Local LLMs: 2025–2026 Guide — Public benchmarks and community reports show the Intel Arc A770 16GB's VRAM headroom fits 7B–14B LLMs natively via IPEX-LLM — at a… 2026-07-12
• Intel IPEX-LLM vs Ollama on AMD: AI Rig Guide 2025 — Intel IPEX-LLM optimizes inference on Intel hardware; Ollama runs anywhere. Here's how each fits into a local AI rig—and when AMD makes… 2026-07-12
• Qwen 3.6 27B Matches Sonnet 4.6 on Artificial Analysis Agency — Qwen 3.6 27B has matched Claude Sonnet 4.6 on Artificial Analysis' Agentic Index — a new benchmark high-water mark for locally deployable… 2026-07-11
• Offline Suitcase Robot: Jetson Orin NX SUPER + Gemma 4 E4B — A community builder documented a fully air-gapped suitcase robot on Jetson Orin NX SUPER 16GB with Gemma 4 E4B, 30+ wired sensors, and… 2026-07-11
• Local Coding Agents: 87% HumanEval with a 4B-Parameter Model — Fine-tuned 4B-parameter models with agentic scaffolding reach 85–87% pass@1 on HumanEval. Here's the hardware, software stack, and… 2026-07-11
• Intel Arc vs NVIDIA 2026: Local LLM Tokens per Dollar — Intel Arc B580, A770 16GB, and Arc Pro B60 24GB vs NVIDIA — community benchmarks and published specs map the tokens-per-dollar gap in 2026… 2026-07-09
• What Is Mistral AI? The OpenAI Rival Explained (2026) — Mistral AI is a Paris-based open-weight LLM company whose models rival GPT-3.5 and run locally on consumer GPUs—here's everything… 2026-07-05
• GLM-5.2: Probably the Most Powerful Text-Only Open-Weights LLM — GLM-5.2 from Zhipu AI challenges GPT-4o and Claude on public benchmarks while remaining fully open-weights — a milestone for local AI… 2026-07-01
• Local LLMs on the Ryzen 5 5600G: llama.cpp CPU Inference Numbers — How fast does a Ryzen 5 5600G actually run local LLMs on CPU with llama.cpp? Real tok/s numbers across 3B, 7B, 8B, and 13B models with… 2026-06-23 · 9 min read
• Intel Axes BigDL/IPEX-LLM: Where Local Inference Goes Now — Intel is winding down BigDL/IPEX-LLM. Here's where to land in 2026 for CUDA, Arc, and CPU-only local LLM inference — with concrete tok/s… 2026-06-23 · 9 min read
• DeepSeek on the US Entity List: What It Means for Local Inference — Would a US Entity List action on DeepSeek stop you from running its models locally on an RTX 3060 or Ryzen APU? Here's what actually… 2026-06-23 · 10 min read
• DeepSeek V4 Pro at $0.04 a Task: When Local Still Beats the Cloud — At $0.04 per task in the cloud, a $1,000 local DeepSeek V4 Pro rig pays itself back at 600-800 tasks per month. 2026-06-16 · 7 min read
• Aider vs Cline vs Cursor for Local Coding on a 12GB GPU (2026) — Aider, Cline, and Cursor compared for local 12 GB GPU coding in 2026. Per-edit latency, model fit, and which to actually install. 2026-06-12 · 8 min read
• DeepSWE vs SWE-Bench Pro: The Coding-Agent Benchmark Shakeup — DeepSWE replaced SWE-Bench Pro at the top of the Coding Agent Index. Here's what changed, why GPT-5.5 scored 31, and how to translate it… 2026-06-12 · 8 min read
• Running Your Own AI Guardrail Model on a 12GB GPU in 2026 — Can a 12 GB GPU host a production AI safety classifier? Yes — with caveats on throughput, quantization, and validation discipline. 2026-06-12 · 8 min read
• OpenAI Buys Ona: What Autonomous Codex Means for Local Coding Rigs — OpenAI bought Ona to push Codex toward autonomous coding. Here's the hardware floor for running that workload locally on a budget 12 GB GPU. 2026-06-12 · 9 min read
• Patch-to-Exploit in Hours: Why a Local Security LLM Rig Now Makes Sense — A practical hardware build for offline LLM-assisted security analysis. What a 12 GB RTX 3060 actually runs for patch-diff and CVE triage… 2026-06-12 · 8 min read
• North Mini Code: The New Small Coding Model and the Hardware That Runs It — North Mini Code is the latest small-coding model on the open-weight leaderboard, and on a 12GB GPU it lands in the comfortable middle: a… 2026-06-10 · 8 min read
• HiDream-O1 1.5 Lands #3 in Text-to-Image: Can You Run It Locally on a 12GB GPU? — HiDream-O1 1.5 just landed at #3 on the Artificial Analysis text-to-image leaderboard, ahead of Nano Banana… 2026-06-10 · 9 min read
• Claude Fable 5 Tops the Intelligence Index: What Frontier Cloud AI Means for Local Rig Builders — Anthropic released Claude Fable 5 and the smaller Mythos 5 today, and Fable 5 now sits at the top of [Artificial Analysis's intelligence… 2026-06-10 · 10 min read
• ComfyUI on a 12GB GPU: SDXL and Flux Setup, VRAM Limits, and Real Throughput — ComfyUI on an RTX 3060 12GB runs SDXL at 14-20s/image and Flux.1 at 30-90s/image with quantized GGUF or fp8 builds. Setup, VRAM limits… 2026-06-09 · 10 min read
• Quantization on a 12GB GPU: q4 vs q5 vs q8 Tok/s and Quality on the RTX 3060 — Quantization on a 12GB GPU in 2026: q4_K_M is the right default for 7B-13B chat, q5 trades 10-15% speed for quality, q8 doubles VRAM for… 2026-06-09 · 10 min read
• Open-WebUI vs LM Studio: Best Local LLM Front-End in 2026 — Open-WebUI vs LM Studio in 2026: LM Studio for single-user desktop simplicity, Open-WebUI for self-hosted multi-user with RAG and tools. 2026-06-04 · 10 min read
• Best SSD for a Local AI / LLM Workstation in 2026 — NVMe Gen3 (WD Blue SN550) for hot model storage + TLC SATA SSD for archives — the best $175 SSD setup for a 2026 AI workstation. 2026-06-04 · 10 min read
• Gemma 4 12B Fits Multimodal AI Into 16GB of RAM — Gemma 4 12B fits in 16GB of unified memory at Q4 — multimodal AI on an APU build at $400 or a 3060 12GB build at $850. 2026-06-04 · 10 min read
• Step 3.7 Flash Benchmarks: What You Can Actually Run on 12GB — Step 3.7 Flash runs cleanly on a 12GB GPU at Q4_K_M with 42 tok/s on a 3060 12GB — making the 12GB tier viable for 14B-total MoE models. 2026-06-04 · 10 min read
• Perplexity's Local-or-Cloud Router: What Hardware Runs the Local Half — Build for Perplexity's 2026 hybrid router: a 12GB RTX 3060 + Ryzen 7 5700X + 32GB RAM hits the local-half latency budget for under $900. 2026-06-04 · 10 min read
• Ideogram 4.0 Open Weights: Native 2K Image Gen on a 12GB GPU — Run Ideogram 4.0 locally on a 12GB GPU at fp8 with VAE tiling: 28-45 seconds per 2K image on a 3060 12GB and a clean sub-$700 build. 2026-06-04 · 10 min read
• Can a Raspberry Pi 4 8GB Run Local LLMs in 2026? Ollama tok/s + SSD-Boot Setup — Can a Raspberry Pi 4 8GB run local LLMs in 2026? Yes — for 1-3B models at 2-5 tok/s with Ollama. We cover the BOM, SSD-boot setup, and… 2026-05-31 · 10 min read
• Best GPU for Training CNNs at Home in 2026: The RTX 3060 12GB Case — Twelve gigabytes of VRAM fits the standard ResNet/EfficientNet/U-Net workloads at usable batch sizes; 8GB cards force compromises. 2026-05-29 · 9 min read
• Ollama vs llama.cpp vs vLLM on an RTX 3060 12GB: Fastest Runtime? — Real numbers: llama.cpp wins single-stream tok/s on an RTX 3060 12GB, Ollama trails by a few percent, vLLM only wins under concurrent load. 2026-05-29 · 10 min read
• Ryzen 7 5800X vs 5700X vs 5600G for a Budget Local-LLM Rig — Which AM4 Ryzen to pair with an RTX 3060 12GB for a budget local-LLM rig? Tested 5800X vs 5700X vs 5600G on tok/s, prefill, and offload. 2026-05-29 · 11 min read
• 768GB Optane Ran a 1T-Param LLM: What It Means for Home Rigs — A 768GB Optane build can technically run a trillion-parameter model — at 0.2 tokens per second. Here's the bandwidth math, and what to… 2026-05-29 · 10 min read
• Intel Arc Pro B70 vs RTX 3060 12GB for Local LLM Inference — Intel's llm-scaler-vllm PV 1.4 makes the Arc Pro B70 a real local-LLM option in 2026. We test it against the RTX 3060 12GB on tok/s… 2026-05-29 · 11 min read
• How to run DeepSeek-R1 32B on Apple M3 Ultra — Fits natively — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for DeepSeek-R1 32B on Apple M3 Ultra. 2026-05-19 · 10 min read
• How to run Qwen 3 32B on Arc B580 — Requires CPU offload — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Qwen 3 32B on Arc B580. 2026-05-19 · 10 min read
• How to run DeepSeek-R1 32B on NVIDIA GeForce RTX 5070 — Requires CPU offload — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for DeepSeek-R1 32B on NVIDIA GeForce RTX 5070. 2026-05-19 · 10 min read
• How to run Qwen 3 32B on NVIDIA GeForce RTX 5070 — Requires CPU offload — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Qwen 3 32B on NVIDIA GeForce RTX 5070. 2026-05-19 · 11 min read
• How to run Qwen 3 14B on Arc B580 — Fits natively — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Qwen 3 14B on Arc B580. 2026-05-19 · 10 min read
• How to run Llama 3.1 70B on NVIDIA GeForce RTX 5070 — Requires CPU offload — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Llama 3.1 70B on NVIDIA GeForce RTX 5070. 2026-05-19 · 10 min read
• AMD Ryzen AI Max+ 395: The 128GB Mini PC Running 70B LLMs Locally — The Ryzen AI Max+ 395's 128GB unified memory pool puts 70B LLMs within reach of a mini PC — but its ~256 GB/s bandwidth, not its capacity… 2026-05-18 · 14 min read
• Half an MI350X in a PCIe Slot: Inside AMD’s 144GB MI350P, the First Air-Cooled CDNA 4 Card — AMD’s MI350P is the first PCIe Instinct accelerator since the MI210 in 2022 — and on paper it is, almost literally, half of an MI350X OAM… 2026-05-08 · 15 min read
• RTX 5090 vs RTX A6000 for Local LLMs: Speed (5090) or Capacity (A6000)? — The 5090 leads dramatically on 8B–32B models; the A6000 is the only sub-$5K card that runs Llama 3 70B Q4 natively. Per-watt analysis and… 2026-05-06 · 11 min read
• NVIDIA RTX PRO 6000 Blackwell vs RTX A6000: Is 96 GB Worth $4,000 More? — RTX PRO 6000 Blackwell ($8,499) beats the A6000 ($4,650) on every benchmark — but two used A6000s with NVLink hit the same 96 GB at half… 2026-05-06 · 13 min read
• NVIDIA RTX A6000 48GB Review: The Workstation Card That Still Owns Local 70B Inference (2026) — The RTX A6000 (~$4,650 new, $2,200-$2,800 on eBay) is two architectures old, but its 48 GB GDDR6 + NVLink combo still owns the budget… 2026-05-06 · 15 min read
• Complete Ollama Installation Guide for 2026: Hardware & Software Setup — Install Ollama on Windows, macOS, or Linux in two commands — then pick the right GPU or Apple Silicon for real tokens-per-second on 7B to… 2026-04-24 · 9 min read
• How to Build a $2000 Home AI Rig in 2026: Used RTX 3090 Guide — Build a $2000 home AI rig in 2026: used RTX 3090, Ryzen 7 7700X on B650, 64GB DDR5, 850W Gold PSU, 2TB Gen4 NVMe — with real tok/s numbers. 2026-04-24 · 11 min read
• Mac Studio M3 Ultra vs RTX 5090 for AI Inference in 2026 — Mac Studio M3 Ultra vs RTX 5090 for AI inference in 2026: unified memory reach, real tok/s numbers, power draw, and who should buy which. 2026-04-24 · 11 min read
• Framework Desktop & Ryzen AI Max+ 395 Review: Best Strix Halo Mini PCs in 2026 — Framework Desktop defined Strix Halo. Here's how the Ryzen AI Max+ 395 actually runs 70B LLMs, plus the 5 best Amazon-available mini PCs… 2026-04-24 · 11 min read
• Jetson Orin Nano Super vs Raspberry Pi 5: Real Edge-AI Benchmarks (2026) — Real tok/s on Llama, Qwen, DeepSeek, Phi: Orin Nano Super at 21.75 tok/s on Qwen2.5-7B; Pi 5 at 5.80 tok/s on Llama 3.2 3B. Full 2026… 2026-04-24 · 11 min read
• Running Llama 3.1 70B Locally: Hardware Requirements & Performance Benchmarks — | Pick | Best For | Key Spec | Price Range | Verdict | |---|---|---|---|---| | Dual NVIDIA RTX 3090 (used) | Solo devs, best value | 48 GB… 2026-04-24 · 11 min read
• DGX Spark vs Mac Studio M3 Ultra: Which AI Dev Machine Wins in 2026? — DGX Spark vs Mac Studio M3 Ultra in 2026: Mac wins on inference (819 GB/s bandwidth, 512 GB ceiling); DGX wins on CUDA training. Real… 2026-04-24 · 14 min read
• NVIDIA DGX Spark Review: Grace Blackwell vs RTX 5090 & Mac Studio M3 Ultra — Compare NVIDIA DGX Spark's 128GB unified memory and Grace Blackwell performance against RTX 5090 rigs and Mac Studio M3 Ultra. Real tok/s… 2026-04-24 · 7 min read
• Best GPU for AI image generation in 2026 — Flux, SDXL, SD 3.5 — Image generation in 2026 is a VRAM race: Flux.1 fp16 wants 24 GB, SDXL wants 12 GB, ControlNet adds 4-6 GB per adapter. Here's the ranked… 2026-04-22 · 11 min read
• Best GPU for an AI rig in 2026 — the shortlist — RTX 5090 is the default single-card buy. 32 GB, mature CUDA, every runtime supports it day one. Mac Studio M3 Ultra is the outlier pick… 2026-04-22 · 11 min read
• Best GPU for AI code generation in 2026 — Code-generation workloads are bandwidth-bound; the right GPU holds a 32B model in VRAM at q4 and pushes 25+ tok/s. Here's the shortlist in… 2026-04-22 · 10 min read
• RTX 5090 vs Mac Studio M4 Max for AI — which wins in 2026? — Max tok/s on a single fits-in-32GB model: RTX 5090 Runs the biggest models you can fit in consumer silicon: M4 Max (128GB) or M3 Ultra (up… 2026-04-21 · 2 min read
• Best Mac for running local LLMs in 2026 — More unified memory wins for LLM work, not CPU core count, not GPU core count. Memory capacity determines which models fit; memory… 2026-04-21 · 2 min read
• VRAM calculator: what can you actually run on your GPU? — At q4KM (the most common community quant), weight size is roughly params × 0.6 bytes: 8B model → 4.8 GB weights + KV cache + overhead → ~6… 2026-04-21 · 2 min read
• How to run Llama 3.1 70B on Apple M3 Ultra — Llama 3.1 70B on Apple M3 Ultra runs at 14–22 tok/s at q4_K_M. Why an M3 Ultra Mac Studio is the cheapest comfortable 70B box in 2026. 2026-04-21 · 12 min read
• How to run Qwen 3 32B on Apple M3 Ultra — Qwen 3 32B on Apple M3 Ultra runs at 28–45 tok/s at q4_K_M with reasoning mode. The cheapest comfortable 32B local-inference setup as of… 2026-04-21 · 12 min read
• How to run Qwen 3 14B on Apple M3 Ultra — Qwen 3 14B on Apple M3 Ultra runs at 55–80 tok/s at q4_K_M with reasoning mode. Why this size beats 8B for agent work, and when not to… 2026-04-21 · 11 min read
• How to run Llama 3.1 8B on Apple M3 Ultra — Llama 3.1 8B on Apple M3 Ultra runs at 75–110 tok/s at q4_K_M — faster than you can read. Install, benchmark, and routing patterns. 2026-04-21 · 10 min read
• How to Run DeepSeek-R1 32B on Apple M4: Which Mac You Need + Real tok/s — DeepSeek-R1 32B on Apple M4 needs at least an M4 Pro 48 GB or M4 Max 36 GB. Expect 18-26 tok/s at q4_K_M. Verified install steps for… 2026-04-21 · 12 min read
• How to run Llama 3.1 70B on Apple M4 — Llama 3.1 70B on Apple M4 needs M4 Max 64GB+ for usable throughput. Full install via Ollama, llama.cpp, or MLX, plus RAM tiers, pitfalls… 2026-04-21 · 11 min read
• How to run Qwen 3 32B on Apple M4 (2026) — Qwen 3 32B on Apple M4 needs an M4 Pro 48 GB+ or M4 Max for usable throughput. Full install guide for Ollama, llama.cpp, and MLX with… 2026-04-21 · 11 min read
• How to run Qwen 3 14B on Apple M4 — Run Qwen 3 14B on Apple M4 at 12–18 tok/s — install via Ollama, llama.cpp, or MLX, plus M4 SKU benchmarks, thinking-mode tips, and when to… 2026-04-21 · 11 min read
• How to run Llama 3.1 8B on Apple M4 — Run Llama 3.1 8B on Apple M4 at 18–29 tok/s — install via Ollama, llama.cpp, or MLX, plus M4 SKU benchmarks, pitfalls, and when 16GB… 2026-04-21 · 11 min read
• How to run DeepSeek-R1 32B on Apple M4 Pro — Run DeepSeek-R1 32B on Apple M4 Pro at 11–17 tok/s — install via Ollama, llama.cpp, or MLX, plus M4 Pro RAM tiers, pitfalls, and when to… 2026-04-21 · 11 min read
• How to run Llama 3.1 70B on Apple M4 Pro — Step-by-step Ollama and llama.cpp setup for Llama 3.1 70B on Apple M4 Pro 64 GB with 10-14 tok/s benchmarks, quantisation choices, and the… 2026-04-21 · 10 min read
• How to run Qwen 3 32B on Apple M4 Pro — Step-by-step Ollama and llama.cpp setup for Qwen 3 32B on Apple M4 Pro 48/64 GB with 20-28 tok/s benchmarks, quantisation choices, and… 2026-04-21 · 10 min read
• How to run Qwen 3 14B on Apple M4 Pro — Step-by-step Ollama and llama.cpp setup for Qwen 3 14B on Apple M4 Pro with 38-55 tok/s benchmarks, thinking-mode controls, and common… 2026-04-21 · 10 min read
• How to run Llama 3.1 8B on Apple M4 Pro (2026) — Llama 3.1 8B on an Apple M4 Pro Mac mini or MacBook Pro: full install commands for Ollama, llama.cpp, and MLX, measured 55-95 tok/s across… 2026-04-21 · 11 min read
• How to run DeepSeek-R1 32B on Apple M4 Max — Step-by-step Ollama and llama.cpp setup for DeepSeek-R1 32B on Apple M4 Max with real tok/s numbers, quantisation trade-offs, and the… 2026-04-21 · 10 min read
• How to run Llama 3.1 70B on Apple M4 Max — Fits natively — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Llama 3.1 70B on Apple M4 Max. 2026-04-21 · 11 min read
• How to run Qwen 3 32B on Apple M4 Max — Fits natively — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Qwen 3 32B on Apple M4 Max. 2026-04-21 · 10 min read
• How to run Qwen 3 14B on Apple M4 Max — Fits natively — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Qwen 3 14B on Apple M4 Max. 2026-04-21 · 9 min read
• How to run Llama 3.1 8B on Apple M4 Max — Fits natively — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Llama 3.1 8B on Apple M4 Max. 2026-04-21 · 10 min read
• How to run DeepSeek-R1 32B on Arc B580 — Arc B580 has 12 GB of GDDR6. DeepSeek-R1 32B at q4KM wants ~19 GB of it for weights alone, plus another 2-3 GB of KV cache at 4K context… 2026-04-21 · 2 min read
• How to run Llama 3.1 70B on Arc B580 — Requires CPU offload — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Llama 3.1 70B on Arc B580. 2026-04-21 · 10 min read
• How to run Llama 3.1 8B on Arc B580 — Arc B580 has 12 GB of GDDR6. Llama 3.1 8B at q4KM is ~4.8 GB of weights alone. Verdict: ✅ Fits natively. Expect ~60-80 tok/s sustained… 2026-04-21 · 2 min read
• How to run Qwen 3 14B on NVIDIA GeForce RTX 5070 — Exact commands, expected tok/s, VRAM math, and the gotchas for running Qwen 3 14B on the RTX 5070 in 2026. 2026-04-21 · 10 min read
• How to run Llama 3.1 8B on NVIDIA GeForce RTX 5070 — NVIDIA GeForce RTX 5070 has 12 GB of GDDR7. Llama 3.1 8B at q4KM wants ~4.8 GB of it for weights alone. Verdict: ✅ Fits natively. Expect… 2026-04-21 · 2 min read
• How to run DeepSeek-R1 32B on AMD Radeon RX 7900 XTX — AMD Radeon RX 7900 XTX has 24 GB of GDDR6. DeepSeek-R1 32B at q4KM wants ~22 GB of it for weights alone. Verdict: ✅ Fits natively. Expect… 2026-04-21 · 2 min read
• How to run Llama 3.1 70B on AMD Radeon RX 7900 XTX — Requires CPU offload — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Llama 3.1 70B on AMD Radeon RX 7900 XTX. 2026-04-21 · 2 min read
• How to run Qwen 3 32B on AMD Radeon RX 7900 XTX — Fits natively — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Qwen 3 32B on AMD Radeon RX 7900 XTX. 2026-04-21 · 2 min read
• How to run Qwen 3 14B on AMD Radeon RX 7900 XTX — Fits natively — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Qwen 3 14B on AMD Radeon RX 7900 XTX. 2026-04-21 · 2 min read
• How to run Llama 3.1 8B on AMD Radeon RX 7900 XTX — AMD Radeon RX 7900 XTX has 24 GB of GDDR6. Llama 3.1 8B at q4KM wants ~4.9 GB of it for weights alone. Verdict: ✅ Fits natively. Expect… 2026-04-21 · 2 min read
• How to run DeepSeek-R1 32B on NVIDIA GeForce RTX 5080 — Requires CPU offload — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for DeepSeek-R1 32B on NVIDIA GeForce RTX 5080. 2026-04-21 · 2 min read
• How to run Llama 3.1 70B on NVIDIA GeForce RTX 5080 — Requires CPU offload — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Llama 3.1 70B on NVIDIA GeForce RTX 5080. 2026-04-21 · 2 min read
• How to run Qwen 3 32B on NVIDIA GeForce RTX 5080 — Requires CPU offload — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Qwen 3 32B on NVIDIA GeForce RTX 5080. 2026-04-21 · 2 min read
• How to run Qwen 3 14B on NVIDIA GeForce RTX 5080 — Fits natively — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Qwen 3 14B on NVIDIA GeForce RTX 5080. 2026-04-21 · 2 min read
• How to run Llama 3.1 8B on NVIDIA GeForce RTX 5080 — NVIDIA GeForce RTX 5080 has 16 GB of GDDR7. Llama 3.1 8B at q4KM wants ~4.8 GB of it for weights alone. Verdict: ✅ Fits natively. Expect… 2026-04-21 · 2 min read
• How to run DeepSeek-R1 32B on NVIDIA GeForce RTX 3090 — NVIDIA GeForce RTX 3090 has 24 GB of GDDR6X. DeepSeek-R1 32B at q4KM wants ~19.2 GB of it for weights, plus ~2-3 GB for KV cache at 4K… 2026-04-21 · 2 min read
• How to run Llama 3.1 70B on NVIDIA GeForce RTX 3090 — Requires CPU offload — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Llama 3.1 70B on NVIDIA GeForce RTX 3090. 2026-04-21 · 2 min read
• How to run Qwen 3 32B on NVIDIA GeForce RTX 3090 — NVIDIA GeForce RTX 3090 has 24 GB of GDDR6X. Qwen 3 32B at q4KM wants ~22 GB of it for weights alone. Verdict: ✅ Fits natively. Expect… 2026-04-21 · 2 min read
• How to run Qwen 3 14B on NVIDIA GeForce RTX 3090 — Fits natively — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Qwen 3 14B on NVIDIA GeForce RTX 3090. 2026-04-21 · 2 min read
• How to run Llama 3.1 8B on NVIDIA GeForce RTX 3090 — NVIDIA GeForce RTX 3090 has 24 GB of GDDR6X. Llama 3.1 8B at q4KM wants ~4.8 GB of it for weights alone (see the full quantization matrix… 2026-04-21 · 2 min read
• How to run DeepSeek-R1 32B on NVIDIA GeForce RTX 4090 — NVIDIA GeForce RTX 4090 has 24 GB of GDDR6X. DeepSeek-R1 32B at q4KM wants ~19.2 GB of it for weights, leaving room for the KV cache… 2026-04-21 · 2 min read
• How to run Llama 3.1 70B on NVIDIA GeForce RTX 4090 — Requires CPU offload — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Llama 3.1 70B on NVIDIA GeForce RTX 4090. 2026-04-21 · 2 min read
• How to run Qwen 3 32B on NVIDIA GeForce RTX 4090 — Fits natively — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Qwen 3 32B on NVIDIA GeForce RTX 4090. 2026-04-21 · 2 min read
• How to run Qwen 3 14B on NVIDIA GeForce RTX 4090 — NVIDIA GeForce RTX 4090 has 24 GB of GDDR6X. Qwen 3 14B at q4KM wants ~10 GB of it for weights alone. Verdict: ✅ Fits natively. Expect… 2026-04-21 · 2 min read
• How to run Llama 3.1 8B on NVIDIA GeForce RTX 4090 — NVIDIA GeForce RTX 4090 has 24 GB of GDDR6X. Llama 3.1 8B at q4KM needs ~4.8 GB for weights alone (about 5.4 GB including a 4K-token KV… 2026-04-21 · 2 min read
• How to run DeepSeek-R1 32B on NVIDIA GeForce RTX 5090 — NVIDIA GeForce RTX 5090 has 32 GB of GDDR7. DeepSeek-R1 32B at q4KM wants ~19 GB of it for weights, plus ~2-3 GB of KV cache at 4K… 2026-04-21 · 2 min read
• How to run Llama 3.1 70B on NVIDIA GeForce RTX 5090 — Requires CPU offload — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Llama 3.1 70B on NVIDIA GeForce RTX 5090. 2026-04-21 · 2 min read
• How to run Qwen 3 32B on NVIDIA GeForce RTX 5090 — Fits natively — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Qwen 3 32B on NVIDIA GeForce RTX 5090. 2026-04-21 · 2 min read
• How to run Qwen 3 14B on NVIDIA GeForce RTX 5090 — Fits natively — step-by-step Ollama and llama.cpp setup plus real tok/s numbers for Qwen 3 14B on NVIDIA GeForce RTX 5090. 2026-04-21 · 2 min read
• How to run Llama 3.1 8B on NVIDIA GeForce RTX 5090 — NVIDIA GeForce RTX 5090 has 32 GB of GDDR7. Llama 3.1 8B at q4KM wants ~4.8 GB of it for weights alone. Verdict: ✅ Fits natively. Expect… 2026-04-21 · 2 min read
• Best GPU for Llama 3.1 405B (2026) — Llama 3.1 405B is a multi-GPU question — the real configurations, costs, and when renting beats building in 2026. 2026-04-21 · 10 min read
• Best GPU for DeepSeek-R1 32B (2026) — Why DeepSeek-R1 32B punishes short contexts, the VRAM math, and the GPUs that handle its long chain-of-thought in 2026. 2026-04-21 · 10 min read
• Best GPU for Llama 3.1 70B (2026) — Multi-GPU and workstation paths that actually run Llama 3.1 70B locally — VRAM math, throughput, and what to skip in 2026. 2026-04-21 · 10 min read
• Best GPU for Qwen 3 32B (2026) — Real benchmarks, full quantization matrix, and the shortlist of GPUs that actually run Qwen 3 32B locally in 2026. 2026-04-21 · 9 min read
• Best GPU for Qwen 3 14B (2026) — Qwen 3 14B needs ~10GB VRAM at q4_K_M. Full quant matrix, real tok/s from the SpecPicks benchmark DB, perf-per-dollar and perf-per-watt… 2026-04-21 · 6 min read
• Best GPU for Llama 3.1 8B (2026) — Llama 3.1 8B needs ~6GB VRAM at q4_K_M. Full quant matrix, real tok/s from the SpecPicks benchmark DB, perf-per-dollar and perf-per-watt… 2026-04-21 · 6 min read