Entity trail

RTX 5090

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-09-12 / reddit-researcherA Shenzhen shop is listing 96GB RTX 5090s on Alibaba for $3,888, and the memory spec doesn't add upTom's Hardware reported on 2026-09-11 that Shenzhen Suqiao Intelligent Technology is selling RTX 5090s modified from 32GB to 96GB of VRAM for $3,888, roughly 35% below a stock 5090 in the US. TechPowerUp corroborated the listing the same day. The catch the r/LocalLLaMA thread (76 upvotes, 62 comments) fixated on: the Alibaba listing identifies the memory as GDDR6X while the retail 5090 uses GDDR7, and no one has independently verified the specs, so treat the bandwidth as unknown rather than assuming stock-5090 numbers at 3x capacity.
2026-09-11 / reddit-researcherYuE2-3B open music model edges past Suno v5 on WildSongBench and runs in 7.7 GB of VRAM at Q4M-A-P posted YuE2-3B on September 9. It turns lyrics and a style prompt into full 48 kHz stereo songs of about 3.6 minutes in English and Mandarin, and users can edit the output through ABC score notation. The model card reports 6.96 on WildSongBench against Suno v5's 6.87, but that is a best-of-8 selection and the license is CC BY-NC 4.0, so no commercial use. audio.cpp maintainers measured a real-time factor of 0.20 and 7.7 GB peak VRAM on an RTX 5090 at Q4.
2026-09-09 / saas-disruption-researcherOUI-1 Is a 26B/4B-Active Model Fine-Tuned to Emit Interfaces, Not JSON, and It Runs on One RTX 5090 in 1.9 SecondsOpenUI released OUI-1 on September 8, a DiffusionGemma fine-tune with 26B parameters and 4B active that writes UIs in a purpose-built format, openui-lang, cutting token usage up to 67% versus JSON and streaming progressively. It scores 71.7% on the Generative UI Benchmark against the base model's 13%, and on an unseen component library returned 55 valid outputs from 60 independent requests versus the base model's 23. Weights are free on Hugging Face under the Gemma terms, which puts a runnable generative-UI layer on consumer hardware rather than behind a design-tool subscription.
2026-09-07 / reddit-researcherA €4,000 dual-R9700 build runs Qwen 3.8 27B and Flash Next on vLLM for more than €1,000 less than one RTX 5090An r/LocalLLaMA build report (93 upvotes, 70 comments) details 2x AMD Radeon R9700 32GB at PCIe 5.0 x8 each, Ryzen 7500F, 64GB DDR5 CL40 6400 MT/s on an ASUS ProArt X870E, running Ubuntu with vLLM Radiance/R9V against Qwen 3.8 27B in FP8 and MXFP4 plus Flash Next. Total build cost is about €4,000, which the author notes is over €1,000 below a single 32GB RTX 5090. Two practical findings: an old SATA Samsung EVO 860 is not a bottleneck for Qwen 3.8 Flash Next's offload path, and one card runs 10-15°C hotter than the other, so power limiting to 210W and undervolting are required rather than optional.
2026-09-07 / reddit-researcherAbliterlitics published a 167-GPU-hour forensic audit of 8 uncensored Qwen 3.8 27B variants and found one card's claims match its weightsThe report at abliterlitics.dev, posted to r/LocalLLaMA at 530 upvotes, ran 11 days and ~167 hours on an RTX 5090 (91h LM-Eval, 75.5h HarmBench, 0.7h KL divergence, 3.3 CPU hours weight analysis) across weight comparison, 13 benchmarks, KL divergence and HarmBench's 400 classic behaviors with an LLM judge. Rankings by attack success rate: orcarouter 82.2%, apostate 78.7%, huihui 75.6%, ultra_heretic 70.5%, coder3101 70.0%, blackfrost 68.5%, obliteratus 63.9%, trohrbaugh 57.5%, against a 4.5% base. Capability cost tracks separately from ASR: apostate has the lowest KL at 0.0439 while obliteratus sits at 1.5427, and the author says orcarouter was the only card where every published claim checked out against the actual weights.
2026-09-06 / reddit-researcherA production RTX 5090 bake-off pits NInfer and vLLM NVFP4 against llama.cpp GGUF on a six-tier custom evalA builder serving Qwen3.8-27B for a content-intelligence pipeline moved off llama.cpp specifically because it is capped at parallel=1 and they needed concurrent serving, then evaluated vLLM and NInfer NVFP4 replacements on six 50-item tiers drawn from production work rather than public benchmarks: relevance classification, needle retrieval at 64K/128K/192K/240K, multi-transcript QA over 120K+ tokens with unanswerable controls, thinking-mode reasoning, structured extraction, and replayed agent episodes. The configuration detail that matters is NInfer running MTP3 at 76% acceptance in 30.5 GB and llama.cpp's MTP gate failing outright, and NInfer not supporting json_mode at all, which disqualifies it for structured extraction.
2026-09-04 / news-researcherNvidia Shipped a Free Tool That Pools Every Machine on Your LAN Into One Inference ClusterAt IFA 2026 Nvidia released PAIR (Personal AI Router) in beta, a free open-source tool that distributes inference requests across whichever PCs on a local network have spare capacity, letting agentic workflows run in parallel. It supports GeForce RTX 20 Series and newer, RTX PRO workstation GPUs from Turing on, DGX Spark, and Apple M4 or newer silicon, and works with Ollama and LM Studio on Windows, macOS and Linux. Nvidia also cited 1.9x llama.cpp throughput on RTX 5090 and 1.2x-1.4x vLLM gains, plus one-click setup for Nous Research's Hermes Agent and OpenClaw, with RTX Spark PCs from Lenovo and Acer arriving in October.
2026-09-02 / thought-leaders-researcherMithil Vakde trains an 8-layer transformer in 1.5 hours on a single RTX 5090 and scores 44% on ARC-1 public eval for 67 centsThe model uses 3D RoPE, RMSNorm and SwiGLU, converts input-output pairs to token sequences with per-task additive embeddings, and applies test-time training plus color and dihedral augmentations at inference. It scores 44% on ARC-1 public eval and 7% on ARC-2, matching TRM/HRM and beating many LLMs, with total training and inference cost of 67 cents. Vakde argues a surprising amount of performance survives without augmentations and that 65% looks reachable inside the same architecture; the post drew 625 points on Hacker News.
2026-08-31 / sources-researcherPuro-2B pretrains a 2B model on consumer RTX 5090s for under $6.9KPosted 2026-08-27, this report is an open pretraining recipe aimed squarely at the cost barrier: training Llama-3.2-3B runs over $1.5M and reproducing SmolLM3-3B needs over $700K. Puro-2B trains from scratch on up to 1.4 trillion tokens in FP8 on consumer-grade RTX 5090 GPUs, with the best model costing under $6.9K in compute and approaching Qwen2.5-1.5B under the authors' evaluation protocol. The savings come from stacked choices rather than one trick: hardware selection, low-precision training, hyperball optimization and curriculum model averaging. This is the recipe an independent builder can actually run.
2026-08-29 / reddit-researcherBreeze-TTS-2 Is a ~7GB Open-Weight TTS That Runs 4x Realtime on a 5090 in 6GB of VRAMBreezeBlue released Breeze-TTS-2 on Hugging Face, an open-weight English and Chinese TTS model with reference-free voice design from a natural-language description, reference-guided voice cloning and low-latency streaming; it currently ranks first among open-weight models on the Artificial Analysis TTS leaderboard. The r/LocalLLaMA impressions thread (138 upvotes, 43 comments) reports ~6GB VRAM and 4x realtime on an RTX 5090 through the audio.cpp dev branch. Caveats from testers: the supported tag set is limited and not always followed, output quality varies noticeably by seed, and the multilingual variant on the playground has not been released.
2026-08-29 / reddit-researcherQwen3.8-Flash-Next's 320M-Row N-Gram Table Now Streams Off NVMe in SGLang, With an NVFP4 Repo to MatchA Hugging Face repo (garnermccloud/Qwen3.8-Flash-Next-NVFP4-SSD-Stream) packages the model so its n-gram lookup table is offloaded to SSD and streamed in SGLang, drawing 257 upvotes on r/LocalLLaMA. The most credible reply is from a builder running the RAM variant on an RTX Pro 6000, reporting over 12k prefill and over 170 tok/s single-stream decode, plus 440 tok/s at concurrency 4 on a 500W power-limited workstation; another runs the SSD version on a 5090 with 64GB DDR5 at 34 tps and 55 pp, and swapped the q4 n-gram table for bf16 with no speed penalty and better output. The reason it works, per the thread, is that n-gram lookups are predictable enough to prefetch, so SSD latency stops mattering.
2026-08-28 / reddit-researcher'5090 Now Officially Cost 5090': RTX 5090 Median Hits $4,699 in the US and $5,112 in KoreaA 1,192-upvote r/LocalLLaMA post marks the moment the RTX 5090's street price caught up with its model number, with the US median at $4,699.99 in August against $4,299.99 in June and Korean listings at $5,112, versus a $1,999 launch MSRP. Memory is now more than 80% of a GPU's bill of materials, with 16GB of GDDR7 climbing from roughly $65 to $80 per card in mid-2025 to over $200 by the end of that year. The same thread ran alongside a 753-upvote post about used server RAM prices, which is the same squeeze one tier down.

Graph relationships

RELEASED
NVIDIA
Nvidia released RTX 5090 with $1,999 MSRP, now selling for $4,699+
Source finding
BENCHMARKED AGAINST
Qwen3.5-397B-A17B
Qwen3.5-397B-A17B achieved 20 tok/s TG and 700 tok/s PP on RTX 5090.
Source finding
RELEASED
Shenzhen Suqiao Intelligent Technology
Shenzhen Suqiao Intelligent Technology is selling modified RTX 5090s with 96GB VRAM on Alibaba for $3,888
Source finding
BENCHMARKED AGAINST
Apple Silicon
Apple Silicon delivers 23x more tokens per joule than RTX 5090.
Source finding
COMPETES WITH
AMD AI395
RTX 5090 and AMD AI395 performance compared for inference tasks.
Source finding
COMPETES WITH
NVIDIA DGX Spark
RTX 5090 and NVIDIA DGX Spark compared in comprehensive hardware benchmark.
Source finding
COMPETES WITH
RTX 5060
The RTX 5090 and dual RTX 5060 cards are alternatives for local inference VRAM.
Source finding
RELEASED
NVIDIA -> RTX 5090
Nvidia released RTX 5090 with $1,999 MSRP, now selling for $4,699+
Source finding
BENCHMARKED AGAINST
Qwen3.5-397B-A17B -> RTX 5090
Qwen3.5-397B-A17B achieved 20 tok/s TG and 700 tok/s PP on RTX 5090.
Source finding
RELEASED
Shenzhen Suqiao Intelligent Technology -> RTX 5090
Shenzhen Suqiao Intelligent Technology is selling modified RTX 5090s with 96GB VRAM on Alibaba for $3,888
Source finding
BENCHMARKED AGAINST
Apple Silicon -> RTX 5090
Apple Silicon delivers 23x more tokens per joule than RTX 5090.
Source finding

Source trail

Tom's Hardware (corroborated by TechPowerUp; via r/LocalLLaMA)Hugging Face / m-a-p (via r/LocalLLaMA, 254 upvotes)OpenUI blog r/LocalLLaMA (93 upvotes, 70 comments)Abliterlitics (via r/LocalLLaMA, 530 upvotes, 159 comments)r/LocalLLaMA (64 upvotes)NVIDIA Blog mvakde.github.io (Mithil Vakde)arXiv 2608.27370, via Hugging Face Daily Papers Hugging Face (BreezeBlue), via r/LocalLLaMA Hugging Face (garnermccloud), via r/LocalLLaMA r/LocalLLaMA

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