How many people have 24gb over gpu here?
Summary
The author discusses the low adoption of the qwen 3.8 27b model based on download counts and estimates that very few users have the high-VRAM GPUs needed for productive local LLM development.
Similar Articles
High VRAM local coding model — still Qwen 3.6 27B?
The user discusses their experience with Qwen 3.6 27B for local coding tasks and asks for recommendations for larger models (100B+) suitable for systems with 224GB of VRAM.
12GB VRAM gang, what's our plan?
Discussion about running LLMs on 12GB VRAM, noting current focus on dense models like Muse Glimmer 30B and Qwen 3.8 27B, and questioning whether upgrading to 24GB VRAM is needed.
@sudoingX: save this one. it answers a question every 24gb GPU owner asks and almost nobody gets right. how much context can i act…
A user shares detailed VRAM usage measurements for running Qwen 3.6 27b on a 24GB GPU, showing context window sizes and headroom, and notes that a used RTX 3090 performs identically to newer cards.
Daniel Han of Unsloth validates Qwen3.8-27B will run only 17GB VRAM
Daniel Han of Unsloth validates that Qwen3.8-27B will run in only 17GB VRAM, making it accessible for local inference.
@sudoingX: anyone running a 16gb card, stop scrolling. @pupposandro and @davideciffa got qwen 35b-a3b down to 13.3gb, measured on …
A technique called luce spark allows Qwen 35B-a3B MoE model to run on a 16GB GPU (like RTX 3090) by learning which experts are frequently used and streaming the rest from RAM, achieving ~100 tok/s without VRAM bottleneck.