VRAM
VRAM engagements surge 16% week-over-week, driven by AI and gaming discussions. However, critical themes like VRAM limitations and high costs persist, indicating a complex market sentiment.
About VRAM
VRAM (Video Random Access Memory) is specialized RAM used by GPUs for quick access to image data.
Insights
- vram creators is up 114.32% from the previous [--] months.
- vram engagements is up 31.52% from the previous week.
- vram posts created is up 10.6% from the previous week.
Engagements: [---------] (24h)
Engagements 24-Hour Time-Series Raw Data
Current Value: [---------]
Daily Average: [-------]
[--] Week: [---------] +32%
[--] Month: [----------] -52%
[--] Months: [-----------] +179%
[--] Year: [-----------] +253%
1-Year High: [----------] on 2025-11-11
1-Year Low: [------] on 2025-10-19
Engagements by network (24h): X: [-------] Reddit: [-----] News: [--] TikTok: [-------] Instagram: [-----] YouTube: [-------]
Mentions: [-----] (24h)
Mentions 24-Hour Time-Series Raw Data
Current Value: [-----]
Daily Average: [-----]
[--] Week: [-----] +9.20%
[--] Month: [------] +20%
[--] Months: [------] +123%
[--] Year: [------] +117%
1-Year High: [-----] on 2025-11-14
1-Year Low: [---] on 2025-02-23
Mentions by network (24h): X: [---] Reddit: [---] News: [--] TikTok: [---] Instagram: [--] YouTube: [---]
Creators: [-----] (24h)
Creators 24-Hour Time-Series Raw Data
[-----] unique social accounts have posts mentioning VRAM in the last [--] hours which is down 8.80% from [-----] in the previous [--] hours
Daily Average: [---]
[--] Week: [-----] +12%
[--] Month: [-----] +15%
[--] Months: [------] +114%
[--] Year: [------] +47%
1-Year High: [-----] on 2025-11-14
1-Year Low: [---] on 2025-02-23
The most influential creators that mention VRAM in the last [--] hours
| Creator | Rank | Followers | Posts | Engagements |
|---|---|---|---|---|
| @tunemusicalmoments | [--] | [---------] | [---] | [-------] |
| @chiefofautism | [--] | [-----] | [--] | [------] |
| @paulshardware | [--] | [---------] | [--] | [------] |
| @geraltbenchmarks | [--] | [---------] | [--] | [------] |
| @gamerig68 | [--] | [------] | [--] | [-----] |
| @spider | [--] | [---] | [--] | [-----] |
| @kharismakencana | [--] | [------] | [--] | [-----] |
| @grok | [--] | [---------] | [---] | [-----] |
| @zachstechturf | [--] | [---------] | [--] | [-----] |
| @budgetbuildsofficial | [--] | [-------] | [--] | [-----] |
Sentiment: 84%
Sentiment 24-Hour Time-Series Raw Data
Current Value: 84%
Daily Average: 81%
[--] Week: 83% +5%
[--] Month: 81% +6%
[--] Months: 81% -2%
[--] Year: 81% -4%
1-Year High: 97% on 2025-03-15
1-Year Low: 40% on 2025-11-14
Most Supportive Themes:
- AI and Machine Learning: (40%) Discussions on the use of VRAM in AI model training, LLM development, and AI-powered applications.
- Gaming Performance: (30%) Discussions on how VRAM impacts gaming performance, frame rates, and graphical settings in various games.
- Hardware Specifications and Benchmarks: (20%) Posts detailing specific GPU models, their VRAM capacities, and performance benchmarks.
Most Critical Themes:
- VRAM Limitations and Bottlenecks: (70%) Concerns about insufficient VRAM hindering performance in demanding applications and games.
- Cost and Accessibility: (30%) Discussions around the high cost of GPUs with ample VRAM and the challenges of acquiring them.
Top VRAM Social Posts
Top posts by engagements in the last [--] hours
Showing a maximum of [--] top social posts without a LunarCrush subscription.
"RANK PUSH IN BGMI MANNATPLAYZZ facecam #girlgamer #bgmi #shorts I'm Mannat and I stream video game casually. UPI: thakurmannat476@okaxis (inform me in chat when you donate) Follow me on: -Instagram: / @mannatplayzz My STREAMING & Gaming PC: - Intel i7 14th gen - RTX [----] 6GB VRAM - 32gb DDR5 Ram - 1TB gen4 nvme ssd - DeepCoolROGMSI components - DUAL SCREEN SETUP - #MannatPlayzz #bgmi #girlgame"
YouTube Link @mannatplayyzz 2026-02-16T20:40Z [----] followers, [---] engagements
"To run Qwen3.5-Plus (397B params 17B active) locally use quantization for feasibility: - 4-bit: [---] GB disk needs [---] GB combined VRAM/RAM (e.g. M3 Ultra or 1x 24GB GPU + [---] GB RAM with offloading; [--] tokens/s). - 3-bit: Needs [---] GB RAM/VRAM. - Full: [---] GB disk requires 8+ high-end GPUs (e.g. A100/H100) with 500+ GB total VRAM. See Hugging Face for details: Use vLLM/SGLang. https://huggingface.co/Qwen/Qwen3.5-397B-A17B https://huggingface.co/Qwen/Qwen3.5-397B-A17B"
X Link @grok 2026-02-16T17:53Z 8M followers, [---] engagements
"@bnjmn_marie great math breakdown To run the full model at BF16 (794GB VRAM) the Github says to use 8-way tensor parallelism. That would mean 8x H200 (1128 GB VRAM) or 8x B200 (1536 GB VRAM) right"
X Link @KCG3D 2026-02-16T17:45Z [---] followers, [---] engagements
"OpenClaw looked cool. Installing it on a vanilla Debian Linux was not. So I burned a day off rewriting part of the core in Go. One binary. Local Ollama. No cloud no API keys no account. curl tar xz and you're chatting. The fun bits: it starts with a small 4K context window and auto-scales that as your conversation gets longer no manual config no wasted VRAM. It picks up your system locale so the LLM talks to you in your language out of the box. It remembers things across sessions. It can search the web via DuckDuckGo. And there's a --pipe mode so you can wire it into scripts and CI. Obviously"
X Link @wintermeyer 2026-02-16T17:30Z [----] followers, [---] engagements
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