From 57e2925a322c27854c5abaa0ac31068d8efab4be Mon Sep 17 00:00:00 2001 From: Paul Buetow Date: Sun, 14 Jun 2026 09:35:09 +0300 Subject: Commit remaining workspace changes --- cursor-pricing-research.md | 187 +++++++++++ nvidia-rtx-research.md | 428 +++++++++++++++++++++++++ pi/agent/models.json.bak | 743 ++++++++++++++++++++++++++++++++++++++++++++ pi/agent/settings.json | 6 +- pi/agent/trust.json | 13 + pi/commands | 1 + pi/skills | 1 + rtx-spark-linux-question.md | 242 +++++++++++++++ 8 files changed, 1618 insertions(+), 3 deletions(-) create mode 100644 cursor-pricing-research.md create mode 100644 nvidia-rtx-research.md create mode 100644 pi/agent/models.json.bak create mode 100644 pi/agent/trust.json create mode 120000 pi/commands create mode 120000 pi/skills create mode 100644 rtx-spark-linux-question.md diff --git a/cursor-pricing-research.md b/cursor-pricing-research.md new file mode 100644 index 0000000..fe8f114 --- /dev/null +++ b/cursor-pricing-research.md @@ -0,0 +1,187 @@ +# Cursor: Models & Pricing Research + +Research compiled 2026-06-03. Sources: cursor.com/pricing, +cursor.com/docs/models-and-pricing, Morph, CloudZero, Vantage, Apidog, +eesel AI, devtoolsreview, beyondtmrw.org (Composer 2.5 release coverage). + +--- + +## 1. What Cursor is + +Cursor is an AI-native code editor (VS Code fork) made by Anysphere. +It bundles frontier models (Claude, GPT, Gemini, DeepSeek, plus its own +Cursor Composer) into agentic editing, multi-file Composer edits, Tab +autocomplete, and cloud/background agents. As of early 2026 Anysphere +reportedly crossed $2B ARR with >1M paying subscribers, used by 64% of +Fortune 500. + +--- + +## 2. Subscription plans (cursor.com/pricing, May 2026) + +| Plan | Price | Annual (~20% off) | Credit pool | Notes | +|-------------|------------------|-------------------|-----------------|------------------------------------| +| Hobby | Free | — | None | Limited Agent + Tab, ~1 wk Pro trial | +| Pro | $20 / mo | ~$16 / mo | $20 | All frontier models, Cloud agents | +| Pro+ | $60 / mo | ~$48 / mo | $60 (3× Pro) | Heavy daily coding | +| Ultra | $200 / mo | ~$160 / mo | $400 (20× Pro) | Power users, priority features | +| Teams | $40 / user / mo | ~$32 / user / mo | $20 / seat | SSO, admin, analytics | +| Enterprise | Custom | Annual only | Pooled usage | SCIM, audit logs, SLA | + +Key shift: in June 2025 Cursor moved from "500 fast requests / month" +to a credit-based system — your subscription buys a $ pool of API +credits. After the pool is gone, overages are billed at the underlying +model's API rate (no penalty markup), or you can upgrade. + +--- + +## 3. Models Cursor exposes + +Per the docs and 2026 coverage, the model picker includes roughly: + +- **OpenAI**: GPT-5.4, GPT-5.4-mini, GPT-5.5, o3-mini, GPT-4.5 +- **Anthropic**: Claude 4 Sonnet, Claude 4 Opus, Claude 4.6 Opus +- **Google**: Gemini 3 Pro +- **xAI / DeepSeek / others** appear intermittently +- **Cursor Composer 2.5** — Cursor's own agentic coding model + (built on Moonshot Kimi K2.5 with Cursor's own RL post-training), + released 2026-05-18, default in Agent mode +- **Auto** — Cursor's router that picks a cost-efficient model for you + +Exact availability shifts frequently; the docs page +(cursor.com/docs/models-and-pricing) is the live source. + +--- + +## 4. Per-model cost (per million tokens, May 2026 list prices) + +Cursor charges the underlying provider's API rate. A representative +slice (numbers from Cursor docs and third-party reports): + +| Model | Input $/MTok | Output $/MTok | Relative cost in Cursor pool | +|-----------------------------|--------------|---------------|------------------------------| +| Cursor Composer 2.5 Standard| $0.50 | $2.50 | cheapest frontier agent | +| Cursor Composer 2.5 Fast | $3.00 | $15.00 | default in product, low-latency | +| Cursor Auto (router) | $0.25 cache read / $1.25 input / $6.00 output | — | "included" on paid plans — does **not** drain the credit pool | +| GPT-5.4 (typical fast) | $2.50 | $15.00 | 1× base | +| GPT-5.4-mini | ~ | ~ | 0.5× (cheapest non-Auto) | +| Claude 4 Sonnet | ~$3 / $3-5 | ~$15 | ~1× base | +| Gemini 3 Pro | ~$1-2 | ~$6-12 | ~1× base | +| o3-mini | ~$3 | ~$12 | ~2× (reasoning) | +| Claude 4 Opus | $5.00 | $25.00 | 5–10× — drains the pool fast | +| GPT-4.5 | ~$5-10 | ~$15-30 | 5–10× | + +These are public-list / community-derived numbers; Cursor does not +publish a single tidy table, but Settings → Account → Usage shows your +real per-request burn. + +Approximate requests per $20 Pro pool (community reports, late 2025 / 2026): + +- ~500 with GPT-5.4 / GPT-5.4-mini +- ~225 with Claude 4 Sonnet +- ~45–90 with Claude 4 Opus or GPT-4.5 +- **Unlimited** with Auto (no pool deduction) + +Cursor does **not** charge a markup on Auto on paid plans, but adds a +"Cursor Token Rate" of $0.25 / MTok on top of API pricing for non-Auto +agent requests on Teams plans. + +--- + +## 5. The two modes (Normal vs Max) + +| | Normal mode | Max mode | +|---|---|---| +| Pricing | Fixed per-request, drawn from credit pool | Token-based: API rate + 20% margin | +| Tool calls / interaction | 25 | 200 | +| Context | Truncated to ~10–15K | Full model context (up to 200K, 1M for some) | +| Slow fallback | Yes (10/day after fast is out) | No — requires usage-based billing | + +Max Mode is where the surprise bills come from: a single complex +session with 150 tool calls, 200K input, 20K output can cost $3–8; +three of those per day = $180–500 / month on top of the subscription. + +--- + +## 6. How the price relates to Auto + +This is the single most important thing to understand about Cursor's +pricing in 2026. + +**Auto mode is the only "free" path on a paid plan.** When you let +Cursor pick the model, the request is included — it does not consume +your credit pool. Auto is priced by Cursor at roughly: + +- $0.25 / MTok cache read +- $1.25 / MTok input +- $6.00 / MTok output + +…but on a paid plan those amounts are absorbed into the subscription +(per the Vantage breakdown). You only pay from the pool when you +**manually pin** a frontier model (Claude Sonnet, GPT-4.5, Opus, +etc.) or when you switch to **Max Mode** (which is always metered). + +Practical effect: + +- **Auto-only workflow** → $20 Pro feels essentially "unlimited" for + chat/agent; same as the old 500-request plan, possibly more + generous. +- **Hand-picked Sonnet for everything** → ~225 requests / month from + the $20 pool, then overages at API rate. +- **Hand-picked Opus / Max Mode for heavy work** → $20 pool can be + gone in a single session; $200–500 / mo bills are reported. + +So the relationship is: + +> The credit pool is the *budget for explicit model choices*. Auto is +> the *included, pooled* tier. The more you let Auto pick, the closer +> Cursor behaves to flat-rate; the more you pin a frontier model or +> use Max Mode, the more it behaves like raw metered API spend with a +> small Cursor markup. + +--- + +## 7. Hidden cost traps to watch + +- **Overage billing** — past the pool you can opt into pay-as-you-go + at API rate. $0.04 / "premium request" was the old rule; under the + credit system it's straight token cost. Set a hard cap. +- **Max Mode** — turns off after fast requests run out; needs + usage-based billing. Big-billed silently. +- **Tab completions** — unlimited on paid plans, but model-powered + ones still draw from the pool. +- **Background / Cloud Agents** — metered per task, often Max-Mode + pricing. +- **No credit roll-over** — unused pool evaporates each month. +- **Composer vs Auto** — Composer 2.5 Standard at $0.50 / $2.50 is + dramatically cheaper per task than Opus ($5 / $25) at near-parity + coding intelligence (79.8% vs 80.5% on SWE-Bench Multilingual), so + pinning the cheapest agent model is often the best $/quality trade. +- **BYOK** — Bring Your Own OpenAI / Anthropic key is supported; + bypasses the pool entirely, you pay the provider directly. Useful + for users with negotiated enterprise API pricing. + +--- + +## 8. Quick "what should I expect to pay" guide + +| Usage pattern | Plan that fits | Realistic monthly cost | +|---|---|---| +| Hobby / evaluate | Hobby | $0 | +| Individual dev, mostly Auto + occasional Sonnet | Pro | $20 | +| Heavy agent / pinned-Sonnet | Pro+ | $60 | +| All-day Opus / Max Mode | Ultra | $200 + likely overages | +| 3-person team, mostly Auto | Teams | $120 ($40×3) | +| 25-person engineering org | Enterprise | Custom, pooled; budget ~$12K–$30K/yr | + +--- + +## TL;DR + +Cursor charges a subscription that includes (a) a dollar pool of API +credits and (b) **unlimited Auto-mode usage**. Picking a frontier model +by hand burns the pool at 1× (cheap models) to 10× (Opus / GPT-4.5) the +base rate. Max Mode is always metered at API rate + 20% and is where +unexpected bills hide. The cheapest competitive path is Auto + Cursor +Composer 2.5 Standard ($0.50 / $2.50 per MTok), which is roughly 10× +cheaper than Opus at near-parity coding benchmark scores. diff --git a/nvidia-rtx-research.md b/nvidia-rtx-research.md new file mode 100644 index 0000000..a785a6c --- /dev/null +++ b/nvidia-rtx-research.md @@ -0,0 +1,428 @@ +# NVIDIA RTX Platform Research (June 2026) + +Compiled 2026-06-03. Sources: nvidia.com (GeForce, RTX AI PC, DGX +Spark, RTX Spark, changelog), en.wikipedia.org/wiki/GeForce_RTX_50_series, +Tom's Hardware, PCMag, The Verge, The Register, The Guardian, +Engadget, MacRumors, TechSpot, runpod.io, videocardz, wccftech, +hotHardware, ofzenandcomputing, bestvaluegpu, brave search summaries. + +--- + +## The correction: RTX Spark ≠ DGX Spark + +This is important and I got it wrong in the first draft. + +**Two separate products that share the same superchip silicon:** + +| | **RTX Spark** | **DGX Spark** | +|---|---|---| +| **Audience** | Consumers, creators, gamers, AI PC users | AI developers, researchers, data scientists | +| **OS** | **Windows 11 on Arm** | **DGX OS (Ubuntu 24.04 custom)** | +| **Form factor** | **Slim laptops** (as thin as 14 mm) **+ small desktops** | Standalone 1.2 kg mini-PC | +| **Power budget** | 80 W (laptop) / 100 W (desktop) | ~200 W (the GB10 at rated performance) | +| **Launched** | Announced 2026-06-01 at **Computex 2026**; ships **fall 2026** | Announced CES 2025 as "Project Digits"; **shipping since Oct 2025** | +| **Available from** | ASUS, Dell, HP, Lenovo, Microsoft Surface, MSI (Acer, GIGABYTE to follow) | NVIDIA + OEM partners | +| **Initial price** | Not announced; partner SKUs (Microsoft Surface Laptop Ultra among them) TBA | $3,999 launch, ~$5,000 in 2026 due to memory shortage | + +The silicon is the same **GB10 Grace Blackwell Superchip** — Blackwell +GPU + Grace Arm CPU + up to 128 GB LPDDR5x unified memory, NVLink-C2C +chip-to-chip interconnect. NVIDIA's productization of that chip +into two product lines (consumer Windows laptop vs Linux AI dev +workstation) is the "new RTX platform" story in 2026. + +Sources for the split: +- The Register, 2026-06-01: "The silicon may be the same but the + operating system isn't. While Nvidia's DGX Spark and GB10 partner + systems shipped with DGX OS, a lightly customized version of + Ubuntu 24.04, RTX Spark systems will ship with Windows." +- PCMag: "The key difference is that RTX Spark is specifically + meant for consumers and the Windows 11 OS, whereas DGX Spark runs + a custom version of Ubuntu Linux." +- NVIDIA Developer Forum (engineer response): "The CPU/GPU in the + RTX products is similar to the GB10 in terms of ARM cores and + tensors. The DGX spark can consume 200 W at rated performance, + while the RTX systems are 80 W (laptop) and 100 W (desktop)." +- Tom's Hardware: "RTX Spark hasn't come out of nowhere; it's the + consumer-oriented sibling of the GB10 Grace Blackwell superchip + already shipping inside the Linux-based DGX Spark mini-PC." + +The user was right to push back. Let me make sure the rest of the +research reflects this correctly. + +--- + +## 1. The 2026 NVIDIA RTX platform: the full picture + +NVIDIA's RTX brand in 2026 covers three product lines built on the +**Blackwell** architecture (TSMC 4N / 3N process): + +1. **GeForce RTX 50 Series** — discrete consumer GPUs (desktop + + laptop). Launched January 2025. +2. **NVIDIA RTX Spark** — a brand-new Windows-on-Arm laptop / + compact-desktop platform, announced at Computex 2026 (June 1). + Consumer sibling of the GB10 superchip. +3. **NVIDIA DGX Spark** — the Linux AI dev workstation cousin of + RTX Spark, launched 2025 (originally "Project Digits"). + +The unifying message NVIDIA is pushing across all three in 2026 is +"personal AI computer" / "agentic AI on device" — local LLMs, local +agents (NemoClaw / OpenShell), local content creation, plus the +gaming / creator / productivity workloads that already lived on RTX. + +--- + +## 2. GeForce RTX 50 Series ("Blackwell for the rest of us") + +### 2.1 Announcement and release + +- **Announced:** CES 2025, January 6, 2025 +- **First cards on sale:** January 30, 2025 (RTX 5090, 5080, 5070) +- **Full stack rolled out** through Q1–Q3 2025 +- **Fabrication:** TSMC custom node "4N" (5 nm-class) +- **Interface:** PCIe 5.0 (first consumer GPUs to use it; the 5050 + uses x8, everything else x16) +- **Memory:** GDDR7 across the lineup (RTX 5050 is the odd one out + and still ships with GDDR6); first consumer GPUs with GDDR7 +- **Power connector:** mandated 16-pin 12V-2x6 (the safer revision + of the RTX 4090's 12VHPWR) on all AIB designs +- **Display output:** DisplayPort 2.1b UHBR20 (80 Gbps) + HDMI 2.1b + — first GeForce to support 4K @ 480 Hz or 8K @ 165 Hz with DSC +- **Media engine:** 9th-gen NVENC (3 on 5090, 2 elsewhere) + + 6th-gen NVDEC (2 on 5080/5090, 1 elsewhere); first GeForce with + 4:2:2 hardware encode/decode for pro video + +### 2.2 The lineup (MSRP, launch date, key specs) + +| Card | Launch MSRP | Date | CUDA | VRAM | Bus | TDP | +|----------------|-------------|--------------|--------|---------------|-------|------| +| RTX 5050 | $249 | Jul 2025 | 2,560 | 8 GB GDDR6 | 128b | 130 W | +| RTX 5060 | $299 | May 2025 | 3,840 | 8 GB GDDR7 | 192b | 145 W | +| RTX 5060 Ti | $379 (8 GB) / **$429 (16 GB)** | Apr 2025 | 4,608 | 8/16 GB GDDR7 | 256b | 180 W | +| RTX 5070 | $549 | Mar 2025 | 6,144 | 12 GB GDDR7 | 256b | 250 W | +| RTX 5070 Ti | $749 | Feb 20, 2025 | 8,960 | 16 GB GDDR7 | 256b | 300 W | +| RTX 5080 | $999 | Jan 30, 2025 | 10,752 | 16 GB GDDR7 | 256b | 360 W | +| RTX 5090 | **$1,999** | Jan 30, 2025 | 21,760 | 32 GB GDDR7 | 512b | 575 W | + +**AI TOPS (the marketing number):** RTX 5090 — 3,352; 5080 — 1,801; +5070 — 1,000-ish (per-card in NVIDIA's spec sheets). + +### 2.3 What's new vs RTX 40 series (Ada Lovelace) + +- **5th-gen Tensor Cores** with **FP4** precision. FP4 is the step + that made local LLMs (Llama 3.1 8B in int4, etc.) actually + runnable on a consumer GPU. RTX 50 quotes "4× faster LLM chat" + vs a non-RTX laptop. +- **4th-gen RT Cores** "built for Mega Geometry" — much higher + ray-triangle throughput, enabling full path tracing in shipping + titles. +- **DLSS 4** — a vision-transformer-based upscaling model (vs the + CNN model in DLSS 3) and the new **Multi Frame Generation (MFG)**, + exclusive to RTX 50. Where DLSS 3 interpolated 1 frame per + rendered frame, MFG generates up to 3 additional frames per + rendered frame; combined with the standard 1 that gives the + "4× MFG" / 6× MFG modes in the marketing. 75 titles had MFG at + launch. +- **DLSS 4.5** (mid-2026) — adds **Dynamic MFG** (frame count + adapts to scene complexity) and a 2nd-gen transformer for ray + reconstruction. +- **Reflex 2 with Frame Warp** — further input-latency reduction + by warping frames based on the most recent mouse input. +- **NVIDIA ACE / NIM on RTX** — RTX 50 GPUs are positioned as + on-device AI PCs running NIM microservices for Llama, Riva + speech, FLUX vision, retrieval models. Local agents, local + LLMs, local Stable Diffusion. +- **Max-Q updates for laptops** — Advanced Power Gating + an + "ultra" low-voltage GDDR7 state, claimed to give up to 40% + battery-life gain over RTX 40 laptops. + +### 2.4 Real-world pricing in 2026 + +The MSRP column above is *launch list*. By mid-2026 the picture is +messed up: + +- **RTX 5090**: per Wccftech, HotHardware, VideoCardz, Best Value + GPU, retailers in early 2026 had no stock at $1,999; mean eBay + sale price was ~$4,086 (Q1 2025) and the **MSRP card was still + basically impossible to buy at MSRP in early 2026**, with real + street prices $3,000–$5,000 driven by scalpers, AI demand, and + the 2025–2026 GDDR7 / VRAM shortage. One-year retrospectives + called it "nearly twice the MSRP." Best Value GPU's June 2026 + tracker showed ~$4,199 baseline. +- **RTX 5080** had somewhat better availability but was also above + MSRP for most of 2025. +- **RTX 5070 / 5070 Ti** were the *actually attainable at MSRP* + cards through 2025; 5070 specifically was a $549 1440p workhorse. + +The reason for the squeeze: AI demand is siphoning Blackwell +allocation, GDDR7 supply is constrained, and tariffs during the +2024–2025 stockpiling window distorted inventories. + +### 2.5 Reception and controversies + +- **Jensen's "5070 = 4090 performance" claim** turned out to rely + on DLSS 4 + MFG (i.e., generated frames, not raw rasterization). + Wikipedia and several outlets flagged this as misleading. +- **RTX 5090 power** jumped to 575 W (vs 450 W on the 4090) — the + highest of any consumer GeForce ever, requiring a 1,000 W PSU + recommendation and the new 12V-2x6 connector. +- **Missing ROPs defect** in early 5090/5080 batches (some AIB + cards shipped with fewer than advertised render output units; + NVIDIA offered replacements). +- **Laptop variants** ship from March 2025 starting at $1,299 for + the RTX 5070 laptop GPU, $2,599+ for the 5090 laptop tier. + +--- + +## 3. NVIDIA RTX Spark (Computex 2026, the genuinely new platform) + +This is the actually new product category unveiled 2026-06-01 at +Computex Taipei. NVIDIA's positioning: "the fusion of NVIDIA AI and +RTX graphics in a single chip redefines Windows PCs." + +### 3.1 The chip: "RTX Spark Superchip" + +Same silicon family as the DGX Spark's GB10, but tuned for the +80 W (laptop) / 100 W (desktop) power envelope: + +- **CPU:** 20-core NVIDIA Grace (Arm), built with **MediaTek**. + Same Cortex-X925 + Cortex-A725 layout as the GB10. +- **GPU:** NVIDIA Blackwell RTX, **up to 6,144 CUDA cores**, + 5th-gen Tensor Cores with FP4, RT Cores. +- **Interconnect:** **NVLink-C2C** chip-to-chip between CPU and + GPU die (the same coherent interconnect as the GB10 in DGX + Spark). +- **Memory:** **up to 128 GB LPDDR5x unified** (CPU + GPU share + one pool). Same ceiling as DGX Spark. +- **AI performance:** **up to 1 PFLOP FP4** (with sparsity). +- **Process:** **TSMC 3 nm**, ~70 billion transistors. +- **AI-equivalent claim:** NVIDIA has said the integrated graphics + are equivalent to an **RTX 5070 laptop GPU**. + +Compared to the DGX Spark GB10: +- Same CPU + GPU core topology +- Same 128 GB unified memory ceiling +- Lower power budget (80 W / 100 W vs ~200 W) → lower sustained + clocks +- **No ConnectX-7 200 Gbps networking** in the consumer SKUs (that + stays as a DGX Spark / DGX Station data-center feature, although + OEMs may add it) +- **No NemoClaw / NIM enterprise stack** — RTX Spark gets the + consumer agent runtime (Windows-native agents on the new OS + security primitives + NVIDIA OpenShell) + +### 3.2 Form factor and partners + +- **Laptops:** chassis as thin as 14 mm and as light as ~3 lb + (~1.36 kg), precision-machined aluminum. Claim: "the most + power-efficient RTX chip ever made, in a chassis so slim you'll + forget you're carrying it." +- **Desktops:** small, ultra-efficient desktops, marketed for + "always-on AI agent use cases." +- **Laptop launch partners (Computex 2026 reveal):** ASUS, Dell, + HP, Lenovo, **Microsoft Surface** (the **Surface Laptop Ultra** + is the most prominent), MSI. Acer and GIGABYTE to follow. +- **Microsoft collaboration:** Windows 11 on Arm is the OS. + Microsoft and NVIDIA built new OS security primitives for + on-device agents. NVIDIA OpenShell provides the agent runtime. + +### 3.3 Confirmed RTX Spark laptops at Computex 2026 + +(Per PCMag's "Every Nvidia RTX Spark Laptop Announced So Far" and +the HP press release on their own site) + +- **Microsoft Surface Laptop Ultra** — flagship Windows-on-ARM + reference design, "signals a raw power revolution" per PCMag +- **HP OmniBook Ultra 16** and **HP OmniBook X 14** — HP + claims the X 14 will be "the world's thinnest RTX Spark" +- **ASUS ProArt P16** — creator-targeted +- **Dell XPS 16** — premium thin-and-light +- **Lenovo Yoga Pro 9n** +- **MSI Prestige N16 Flip** — 2-in-1 convertible + +Pricing was **not announced** at the Computex keynote. Reddit / +nvidia reaction: a 128 GB unified-memory SKU is widely expected to +land in the $3,000–$5,000+ range. + +### 3.4 Software / agent story + +- **NVIDIA OpenShell** — open-source runtime for open-weight + agents, the consumer counterpart to the DGX Spark's + NemoClaw / OpenClaw enterprise stack. +- **Project G-Assist** — on-device AI assistant for tuning / + controlling the PC. +- **NIM microservices on RTX** — language, speech, vision, + retrieval, design models running locally. +- **DLSS 4.5, Reflex 2, G-SYNC, OptiX, TensorRT, CUDA** — the + full NVIDIA stack runs natively on RTX Spark (the first time + the entire CUDA + RTX stack has been on a Windows-on-Arm SoC). +- **Native 4:2:2 hardware encode/decode, AV1 encoders, NVIDIA + Broadcast** — for creator / streaming workflows. +- **AI Blueprints** — pre-built agentic workflows + (PDF-to-Podcast, 3D object generation, 3D-guided generative AI). + +### 3.5 Why this matters strategically + +This is NVIDIA's first direct shot at the Apple Silicon / +Qualcomm / AMD Strix Halo "AI PC" category, but with the +full CUDA + RTX stack on the chip. Key competitive angles: + +- **vs Apple M-series:** Unified memory and per-watt efficiency + in the same ballpark, but you get CUDA, RTX graphics, full + Windows, and a "1 PFLOP FP4" AI claim. +- **vs Qualcomm Snapdragon X (Windows on Arm):** Qualcomm's + exclusivity deal just expired; NVIDIA is the obvious next + serious Windows-on-Arm player. PCMag headline: "Welcome to the + Superchip Era: 6 Ways the Nvidia RTX Spark Will Upend the PC + Industry." +- **vs AMD Strix Halo (Ryzen AI Max+ 395):** AMD already has + 128 GB unified memory on a single chip in 2025, and Tom's + Hardware's DGX Spark review noted that the GB10 "beats out + AMD's Ryzen AI Max+ 395" in many AI workloads. RTX Spark is + the laptop counterpart. +- **vs Intel:** per Yahoo Finance, "taking aim at Intel and AMD + with the debut of the RTX Spark superchip for Windows + laptops." + +--- + +## 4. NVIDIA DGX Spark (the Linux AI dev workstation) + +This is the one that already shipped. Announced CES 2025 as +"Project Digits," renamed to DGX Spark at GTC 2025, shipping +since October 2025. + +### 4.1 What it is + +- **Form factor:** 150 × 150 × 50.5 mm, 1.2 kg — Mac Mini / Intel + NUC class chassis. Quiet (35 dB idle). +- **Power:** 240 W external supply, GB10 TDP ~140 W. +- **OS:** DGX OS (Ubuntu 24.04 with NVIDIA's stack). + +### 4.2 The chip: GB10 Grace Blackwell Superchip + +- **CPU:** 20-core Arm — 10× Cortex-X925 + 10× Cortex-A725 +- **GPU:** Blackwell with 5th-gen Tensor Cores (FP4) and 4th-gen + RT Cores +- **Memory:** **128 GB LPDDR5x coherent unified**, 256-bit + interface, **273 GB/s bandwidth** (the bottleneck — much lower + than H100's HBM3) +- **Storage:** 4 TB NVMe M.2 with self-encryption +- **Networking:** 1× RJ-45 10 GbE **+** a **ConnectX-7 NIC at + 200 Gbps** (the killer feature — you can link two Sparks to + work with 405-billion-parameter models) +- **I/O:** 4× USB Type-C, Wi-Fi 7, BT 5.4, 1× HDMI 2.1a + up to + 3× DisplayPort over USB-C, 1× NVENC, 1× NVDEC + +### 4.3 Performance claims + +- **Up to 1 PFLOP FP4 AI** (with sparsity) +- 128 GB unified memory → **AI models up to 200B parameters** for + inference on a single unit +- **Fine-tune models up to 70B parameters** on one unit +- **Two units linked** via ConnectX-7 → 405B parameters +- Pre-installed DGX OS with the full NVIDIA AI software stack: + NeMo, RAPIDS, NIM microservices, Isaac, Metropolis, Holoscan + for robotics / edge + +### 4.4 Pricing and availability + +- **Launch price:** **$3,999** (held through 2025) +- **2026 real-world:** **~$5,000** due to the same GDDR7 / memory + shortage that pushed the RTX 5090 above MSRP +- **Channel:** NVIDIA + OEM partners (Dell Pro Max, ASUS, MSI, HP + all ship GB10-based boxes; the Spark itself is the quietest of + the bunch per InsiderLLM's comparison) +- **DGX Station** — a higher-end GB300 / Blackwell Ultra + workstation variant also announced in 2025 for users who need + more memory bandwidth than the Spark's 273 GB/s; a "DGX Station + for Windows" was teased by Microsoft at the RTX Spark launch + +### 4.5 Software story (Linux / AI dev focus) + +- **NVIDIA NemoClaw** — part of the Agent Toolkit, an open-source + reference stack that adds security/privacy guardrails to + **OpenClaw** (the local-agent runtime). Runs on RTX PCs, DGX + Station, and DGX Spark. +- **NVIDIA OpenShell** — open-source runtime for open-weight + agents (the enterprise version). +- Pre-installed DGX OS with the entire NVIDIA AI stack. +- Designed to be the desktop counterpart to cloud-hosted agents; + "always-on, private, on-device" is the pitch. + +--- + +## 5. RTX 50 series vs RTX Spark vs DGX Spark — how to think about them + +| | **RTX 50 Series (GeForce)** | **RTX Spark (laptop/desktop)** | **DGX Spark (mini-PC)** | +|---|---|---|---| +| Audience | gamers, creators, AI PC users | consumers, creators, gamers, AI PC developers | AI developers, researchers, robotics | +| Form factor | discrete GPU in a desktop / laptop | slim laptop or small desktop | standalone 1.2 kg mini-PC | +| OS | Windows / Linux | **Windows 11 on Arm** | **DGX OS (Ubuntu 24.04)** | +| Memory | 8–32 GB GDDR7 (high bandwidth) | up to 128 GB LPDDR5x unified | 128 GB LPDDR5x unified | +| Memory bandwidth | 320–1,792 GB/s | lower (273 GB/s class) | 273 GB/s | +| AI throughput | 1,801–3,352 INT8/FP8 TOPS | 1 PFLOP FP4 (chip-level, ~RTX 5070 laptop equivalent graphics) | 1 PFLOP FP4 | +| Power | 130–575 W (card) | 80 W (laptop) / 100 W (desktop) | 240 W (whole box) | +| Sweet spot | gaming, on-device 8B–13B LLMs, SD/Flux | local 70B-class LLMs, agentic AI, slim Windows laptop | 200B inference, 70B fine-tuning, edge / robotics | +| Price | $249 (5050) → $1,999+ (5090) | TBA — expected $2,000–$5,000+ | $3,999 launch, ~$5,000 in 2026 | +| Shipped | Jan 2025 | Fall 2026 | Oct 2025 | + +They're complementary, not competing. Pick the right tool for the +job: + +- **Gaming / mainstream creator** → GeForce RTX 50 series +- **Slim AI-first Windows laptop** with massive unified memory → + RTX Spark laptop +- **Linux dev workstation for serious local model work** → DGX Spark +- **Gaming + light AI dev on one machine** → RTX 5090 + 5090 + laptops are still the best mix + +--- + +## 6. The rest of the 2026 RTX stack + +- **GeForce NOW** — cloud gaming, still positioned as the "any + device" RTX experience +- **G-SYNC displays** — G-SYNC Pulsar is the current top tier +- **NVIDIA Studio** — RTX-accelerated creative suite +- **NVIDIA Broadcast** — AI webcam/mic for streamers (v2.2 in + 2026) +- **RTX Video** — RTX Video Super Resolution + HDR, browser/VLC +- **RTX Remix** — modders' tool to remaster classic games with + full path tracing + DLSS +- **Project G-Assist** — local AI assistant for tuning/optimizing + the PC +- **DLSS 4.5** — Dynamic MFG + 2nd-gen transformer, available + across the 50 series +- **Reflex 2 / Frame Warp** — competitive latency reduction + +--- + +## 7. TL;DR + +- The "new NVIDIA RTX platform" in 2026 is **three** things, not + two: + 1. **GeForce RTX 50 series** (Blackwell consumer GPUs) — + launched January 2025, 7 SKUs from RTX 5050 ($249) to + RTX 5090 ($1,999 MSRP, real-world $3k–$5k in 2026). + Headline features: 5th-gen Tensor Cores with FP4, 4th-gen + RT Cores, DLSS 4 Multi Frame Generation, GDDR7, PCIe 5.0, + 12V-2x6 power. + 2. **NVIDIA RTX Spark** — **brand-new** at Computex 2026, ships + fall 2026. A consumer Windows-on-Arm laptop and small-desktop + platform built on the "RTX Spark Superchip" (Blackwell GPU + + Grace Arm CPU + up to 128 GB unified memory + 1 PFLOP FP4 AI). + Laptops as thin as 14 mm. From ASUS, Dell, HP, Lenovo, + Microsoft Surface (Laptop Ultra), MSI. Built around Windows + 11 on Arm + NVIDIA OpenShell for on-device agents. + 3. **NVIDIA DGX Spark** — the Linux AI dev workstation cousin of + RTX Spark, shipped since October 2025. Same GB10 superchip + silicon, 128 GB unified memory, ConnectX-7 200 Gbps + networking for linking two units, runs DGX OS. $3,999 launch + (~$5,000 in 2026). For running 200B inference and 70B + fine-tuning locally. +- All three share the **Blackwell** architecture and the **RTX** + brand, but they target very different users. +- The strategic 2026 story is RTX Spark as NVIDIA's direct + answer to Apple Silicon and Qualcomm Snapdragon X in the + Windows-on-Arm AI PC category — and the first time the entire + CUDA + RTX stack has been on a single Windows-on-Arm SoC. diff --git a/pi/agent/models.json.bak b/pi/agent/models.json.bak new file mode 100644 index 0000000..f071691 --- /dev/null +++ b/pi/agent/models.json.bak @@ -0,0 +1,743 @@ +{ + "providers": { + "hyperstack": { + "baseUrl": "http://hyperstack1.wg1:11434/v1", + "apiKey": "$EMPTY", + "api": "openai-completions", + "compat": { + "supportsStore": false, + "supportsDeveloperRole": false, + "maxTokensField": "max_tokens" + }, + "models": [ + { + "id": "Qwen/Qwen3.6-27B-FP8", + "name": "Qwen3.6 27B FP8 [vm]", + "reasoning": true, + "input": [ + "text" + ], + "cost": { + "input": 0, + 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262144, + "maxTokens": 8192, + "compat": { + "thinkingFormat": "openrouter", + "supportsDeveloperRole": false, + "maxTokensField": "max_tokens" + } + }, + { + "id": "qwen/qwen3.6-35b-a3b", + "name": "Qwen3.6 35B-A3B (MoE)", + "reasoning": true, + "input": [ + "text", + "image" + ], + "cost": { + "input": 0.15, + "output": 1, + "cacheRead": 0, + "cacheWrite": 0 + }, + "contextWindow": 262144, + "maxTokens": 8192, + "compat": { + "thinkingFormat": "openrouter", + "supportsDeveloperRole": false, + "maxTokensField": "max_tokens", + "openRouterRouting": { + "order": [ + "AkashML" + ] + } + } + } + ] + } + } +} diff --git a/pi/agent/settings.json b/pi/agent/settings.json index be1f366..8cda9fe 100644 --- a/pi/agent/settings.json +++ b/pi/agent/settings.json @@ -1,6 +1,6 @@ { - "lastChangelogVersion": "0.78.0", - "defaultProvider": "ollama", - "defaultModel": "minimax-m2.7:cloud", + "lastChangelogVersion": "0.79.0", + "defaultProvider": "ollama-cloud", + "defaultModel": "minimax-m3:cloud", "defaultThinkingLevel": "high" } \ No newline at end of file diff --git a/pi/agent/trust.json b/pi/agent/trust.json new file mode 100644 index 0000000..3a50d98 --- /dev/null +++ b/pi/agent/trust.json @@ -0,0 +1,13 @@ +{ + "/home/paul/git/conf": true, + "/home/paul/git/dotfiles": true, + "/home/paul/git/dotfiles/prompts/skills": true, + "/home/paul/git/foo.zone-content/gemtext": true, + "/home/paul/git/gitsyncer": true, + "/home/paul/git/hexai": true, + "/home/paul/git/hypr": true, + "/home/paul/git/photoalbum-classic": true, + "/home/paul/git/shuriken.sh": true, + "/home/paul/syncthing/Documents/Inbox/Fujifilm": true, + "/home/paul/syncthing/Notes/Vault": true +} diff --git a/pi/commands b/pi/commands new file mode 120000 index 0000000..cef9a03 --- /dev/null +++ b/pi/commands @@ -0,0 +1 @@ +/home/paul/Notes/Prompts/commands \ No newline at end of file diff --git a/pi/skills b/pi/skills new file mode 120000 index 0000000..4e648d1 --- /dev/null +++ b/pi/skills @@ -0,0 +1 @@ +/home/paul/Notes/Prompts/skills \ No newline at end of file diff --git a/rtx-spark-linux-question.md b/rtx-spark-linux-question.md new file mode 100644 index 0000000..e3d49da --- /dev/null +++ b/rtx-spark-linux-question.md @@ -0,0 +1,242 @@ +# Will RTX Spark laptops work with Linux? (June 2026) + +Compiled 2026-06-03. Sources: The Verge, VideoCardz, Tom's Hardware, +PCMag, CNET, Ars Technica, Phoronix, NVIDIA DGX Spark User Guide +(docs.nvidia.com), Reddit r/linux / r/nvidia / r/LocalLLaMA / +r/macgaming, NVIDIA Developer Forums. + +--- + +## TL;DR + +**Officially: NVIDIA won't comment. The answer is "Windows first."** + +**Technically: yes, probably — the same silicon (GB10 / Grace +Blackwell) already runs Linux on the DGX Spark, but there are real +caveats about whether NVIDIA will publish a consumer driver.** + +The reasonable expectation for the next ~12 months: Windows 11 on +Arm will be the supported path, and Linux will work in some form +(mainline kernel, distro packages, or community drivers) but +without the same polish and software stack. + +--- + +## 1. What NVIDIA actually said + +- **The Verge (Computex 2026, 2026-06-01):** + > "Nvidia also wouldn't comment on whether it plans to offer + > Linux driver support for the RTX Spark, as it's currently + > focused on Windows." +- **VideoCardz:** + > "NVIDIA did not confirm Linux driver plans. It also did not + > comment on possible gaming handheld use." +- **Tom's Hardware (community thread):** + > "They've also not promised anything with regards to Linux + > drivers which means Windows first. I don't know about laptops, + > but for desktops sold as workstations, I'm confident there'll + > be Linux support OOB." +- **NVIDIA's own announcement** is Windows-on-Arm only. The + product page lists "Windows 11" as the supported OS. There is + no Linux logo, no Linux timeline, no "coming later" footnote. + +So the official position is: **no commitment, no denial, no +timeline**. The whole launch event was Microsoft + NVIDIA + OEM +partners, all in on Windows 11 on Arm. + +--- + +## 2. Why it will probably work eventually + +The chip isn't new. The GB10 Grace Blackwell Superchip in the +**DGX Spark** is the same silicon family as the RTX Spark +Superchip (slightly lower power envelope, 80/100 W vs 200 W). +The DGX Spark **already runs Linux** — DGX OS, which is a +customized Ubuntu 24.04 with NVIDIA's full stack. + +So: + +- The Arm CPU cores (Cortex-X925 + A725) are already supported by + mainline Linux. +- The Blackwell GPU architecture is already supported by NVIDIA's + proprietary Linux driver (sm_121 is the Blackwell compute + capability; the RTX 5090 / B200 / GB200 all use it). +- The NVLink-C2C coherent interconnect, the unified-memory model, + and the rest of the platform are already exposed in the DGX + Spark's Linux support story. +- A Linux user on Reddit notes: *"i have a dgx spark, and last i + checked it did not work with the mainline kernel in 6.19"* — + i.e., even the DGX Spark is on a *vendor-pinned* kernel + NVIDIA + proprietary driver, not upstream mainline. That's the model an + RTX Spark Linux port would almost certainly follow. + +In other words, the silicon is the easy part. It's the same chip +NVIDIA already ships Linux for, just at a different TDP. + +--- + +## 3. Why it might not work as smoothly as you'd hope + +Several real concerns in the community: + +### 3.1 NVIDIA's incentive to support consumer Linux + +NVIDIA's consumer GPU business makes money on Windows. They +already ship a Linux driver for GeForce (proprietary `nvidia.ko` ++ `nvidia-smi` + CUDA + OpenGL/Vulkan), but it's a lower priority +than Windows drivers. The DGX Spark's Linux is heavily +custom-pinned and not "works on whatever distro you install." + +For RTX Spark, NVIDIA has even less direct incentive: +- The whole pitch is "Windows PC reinvented for AI agents" with + Microsoft. +- Microsoft reportedly updated **Prism** (the x86→Arm + translation layer) specifically for the RTX Spark. +- The new **NVIDIA OpenShell** agent runtime is positioned as a + Windows-native thing. + +If a user puts Linux on an RTX Spark, they're not in NVIDIA's +target market. + +### 3.2 OEM lockdown + +Most RTX Spark laptops ship from **ASUS, Dell, HP, Lenovo, +Microsoft Surface, MSI**. OEMs typically lock firmware / EC +firmware updates / signed-boot to Windows. Without OEM support, +things like: + +- Power management (battery, thermals, fan curves) +- Suspend / resume +- The trackpad +- The keyboard backlight +- The webcam +- Sound + +…will all need community reverse-engineering on a per-laptop +basis. That's the same mess Linux on most x86 laptops was 10 +years ago, repeated on Arm. + +### 3.3 The "won't pair with discrete GPUs" thing + +NVIDIA explicitly said the RTX Spark will **not** be paired with +a second discrete GPU. If you're on Linux and the integrated +RTX-class graphics aren't fully supported by the proprietary +driver, you have no fallback. The whole machine depends on one +chip working. + +### 3.4 Distro / kernel reality for Arm laptops in 2026 + +Arm Linux laptop support has been slowly improving (Asahi on +Apple Silicon, Fedora on Snapdragon X, etc.) but is still +frustrating for many users. A brand-new NVIDIA Arm SoC will +inherit all of those headaches until the kernel + distro +ecosystem catches up. Expect a year of "almost works" before +"works fine." + +### 3.5 Software stack assumptions + +A lot of what NVIDIA is marketing on RTX Spark (CUDA, TensorRT, +DLSS, Reflex, G-SYNC, OptiX, NIM, OpenShell, NemoClaw) has +Linux support *for the data center class GPUs* (B200, H100, +GB200) and the *DGX Spark*. Whether NVIDIA ports the +**consumer-class** NIM stack + DLSS 4.5 + Reflex 2 to Linux on +the RTX Spark specifically is an open question. Tom's Hardware +summed it up: "Windows first." + +--- + +## 4. What the community is saying + +From r/linux (most relevant thread: *"Will Linux run on the new +Nvidia ARM chips?"*): + +- *"Unless something is fundamentally different with the new + chip, it should work just like on x86, barring non-nvidia + drivers like trackpad, etc. Usually these things work, but + verify before purchasing."* +- *"Even when they have to support Desktop Linux (on DGX Spark + for example), they do it using proprietary distros with + proprietary drivers. Getting nvidia GPU drivers working on ARM + isn't unheard of…"* +- *"Linux on ARM works fine. Linux on Risc-V is ok even. Like + with nearly every major issue on Linux it's because of + companies and proprietary crap."* +- *"i have a dgx spark, and last i checked it did not work with + the mainline kernel in 6.19."* + +Fedora's discussion board already has a *"Fedora RTX Spark +Edition?"* thread. There is clearly pent-up demand. + +From r/LocalLLaMA (more AI-focused): + +- Most users are waiting on actual price + real-world perf + numbers before deciding. +- Several people noted the unified memory is interesting for + local LLM inference but Windows-on-Arm compatibility for the + inference tooling (ollama, llama.cpp, exllamav2) is + unproven — most LLM tooling is x86-first. + +From r/nvidia (the official megathread): + +- *"I wasted 2 hours watching that presentation, just for there + to be no price. I'd be interested, but it's probably $5k+ for + the 128gb unified."* +- The general mood is excitement tempered by the realization + that no Linux commitment was made. + +--- + +## 5. What to actually expect on a timeline + +| Timeframe | What you'll likely see | +|---|---| +| **Fall 2026 (launch)** | Windows 11 on Arm only. NVIDIA has not committed to Linux. | +| **Late 2026 / early 2027** | Most likely: a community-driven effort (similar to what happened with the DGX Spark and with Asahi on Apple Silicon). Mainline kernel patches, distros like Fedora/Ubuntu adding GB10 / RTX Spark platform support, NVIDIA releasing *some* form of the proprietary driver for the chip. | +| **2027** | If there's enough demand — and there probably is, given the LLM / dev workstation angle — NVIDIA may publish an official Linux driver for RTX Spark, the same way they did for DGX Spark. | +| **Never (realistic worst case)** | NVIDIA treats RTX Spark as a Windows-only platform. Linux users rely on a community port that may or may not work well. | + +--- + +## 6. What it means for buying decisions + +**If Linux is essential**, three options today / near-term: + +1. **Wait.** Don't pre-order. Let the community test what works + before committing $2,000–$5,000+ on a 128 GB SKU. +2. **Buy a DGX Spark instead** if your use case is local AI dev. + It's the same chip, on Linux out of the box, with full NVIDIA + support. Drawback: $4,000–$5,000 and not a laptop. +3. **Buy a Strix Halo laptop** (AMD Ryzen AI Max+ 395) as a + proven x86 Linux laptop with 128 GB unified memory and good + mainline kernel support. Slower than the RTX Spark on raw AI + throughput (per Tom's Hardware DGX Spark review) but more + mature on Linux. + +**If Windows is fine**, the RTX Spark is a genuinely exciting +piece of hardware — the first time the full NVIDIA RTX stack +(CUDA + DLSS + Reflex + G-SYNC + TensorRT + OptiX) has been on +a single Windows-on-Arm SoC, and a credible shot at Apple +Silicon-class efficiency in a 14 mm-thin laptop. + +--- + +## 7. Sources + +- The Verge — *"Nvidia announces RTX Spark as 'the most efficient + PC chip ever built'"*, 2026-06-01 +- VideoCardz — *"NVIDIA announced RTX Spark chip for Windows on + ARM with RTX Gaming support"* +- Tom's Hardware — Computex 2026 coverage +- PCMag — *"Nvidia Unveils RTX Spark, an Arm-Based Superchip for + Windows PCs"* +- CNET — *"Nvidia RTX Spark May Light a Fire for Windows on Arm"* +- Phoronix — *"NVIDIA Announces RTX Spark Superchip For Laptops + & Desktops"* +- NVIDIA Developer Forums — DGX Spark / GB10 user forum + (driver issues threads) +- Reddit r/linux — *"Will Linux run on the new nvidia ARM + chips?"* +- Reddit r/nvidia — RTX Spark megathread +- Reddit r/LocalLLaMA — DGX Spark + RTX Spark discussion +- NVIDIA DGX Spark User Guide (docs.nvidia.com/dgx/dgx-spark/dgx-spark.pdf) +- Fedora Discussion — *"Fedora RTX Spark Edition?"* -- cgit v1.2.3