Local Ai
Qwen3.8-27B FP8 dual GPUs
Hardware RTX 5090 (32 GB) + RTX 4070 Ti Super (16 GB) = 48 GB VRAM 32 GB DDR5 6200 RAM Arch Linux, KDE on the 5090 (takes ~1-1.5 GB VRAM) daily driver OrcaRouter Qwen3.8-27B Uncensored, block-FP8 (28.
Hardware RTX 5090 (32 GB) + RTX 4070 Ti Super (16 GB) = 48 GB VRAM 32 GB DDR5 6200 RAM Arch Linux, KDE on the 5090 (takes ~1-1.5 GB VRAM) daily driver OrcaRouter Qwen3.8-27B Uncensored, block-FP8 (28.75 GiB), on vLLM 0.30.0 with pipeline parallel across both cards 4070 = rank 0 with layers 0-19 + vision encoder, 5090 = rank 1 with layers 20-63 + lm_head + MTP. Full 262,144 context, MTP K=3, fp8 KV, 2 slots. Benchmarks (vLLM 0.30.0, vllm bench serve) 1K in / 512 out, c1, random 81.3 tok/s, ITL 36.7 ms (~100 tok/s on code) MTP acceptance ~87% 32K prefill 3,160 tok/s 145K fresh prefill 68.5-68.8 s 258K prefill 169 s, 5090 peak 31,472 MiB The 4070Ti Super was collecting dust for 2 months because i thought Pcie x1 will slow it but apparently not submitted by /u/Fz1zz [link] [comments]
Related
- CyberTiel 35B-A3B’s uncensored 4-bit quant beats Opus 4.6 medium cleanly on real codebase issues, in 27% of the time Qwen3.8-27b medium takes.
- Rumored 50-series Super refresh bumps everything +50% VRAM
- Qwen3.6 27B on dual RTX 5060 Ti 16GB with vLLM: ~60 tok/s, 204k context working
- What are the current best retail GPUs for max VRAM at a reasonable price?
Source: r/LocalLLaMA | 2026-09-27