Growing context windows and larger local models are making video memory and RAM the critical constraint for self-hosted inference. Reports of 64/96 GB RTX 5090 cards, million-token Qwen 4 models, and new agent workloads show 64 GB is no longer enough.
The rumor about GeForce RTX 5090 with 64 and 96 GB of VRAM hits the critical bottleneck for local LLM users: video memory. An analysis of implications for self-hosted deployments, quantization, TCO, and data sovereignty, beyond the hardware announcem...
A US GPU repair technician has reportedly claimed the existence of RTX 5090 cards with 64 and 96 GB of VRAM. The unverified rumor touches the core constraint for local inference: more video memory enables larger models, less aggressive quantization, ...
A Mac M4 Max test with a Qwen3.8 27B model and 164k tokens of context shows cache and KV can cost as much as weights. The old 64GB rule no longer holds.
The pull request in qwen-code signals that Qwen4 targets a one-million-token window. For self-hosted inference the cost is not theoretical: the key-value cache grows with tokens and fills VRAM along with weights. Qwen4-27B makes multi-GPU setups or a...
Alibaba brings Qwen4 to a one-million-token context window. The news emerges from a pull request in qwen-code: Qwen4-27B is expected tomorrow at the Apsara event in the Netherlands, while Qwen4-max is dated November 1st with October 1st as a likely p...
