Model Releases
Improve token per second without touching quant
Spent the past month tweaking and experimenting with many different numbers to achieve 30tps. Hardware: -Rx6700xt 12gb vram (AMD) -2x16 ddr4 3200 ram -r5 5600x -llama.cpp vulkan sdk -window11 (no wsl
Spent the past month tweaking and experimenting with many different numbers to achieve 30tps. Hardware: -Rx6700xt 12gb vram (AMD) -2x16 ddr4 3200 ram -r5 5600x -llama.cpp vulkan sdk -window11 (no wsl switching since im not used to the environment) Im looking for any improvements to achieve maybe 40tps? without touching quant at all, q8 and q4_k_xl remains. I've experiment with threads at 6 is the best out of (4,8,12) Other than that im not sure on what to improve to achieve higher tps, any advices? appreciate it. ctx remains 100,000 |[tiel-coder-35b] model = C:Usersrainlmstudiomodelspeculiar-ragdollTiel-Coder-35B-A3B-GGUF-MTPTiel-Coder-35B-A3B-MTP-UD-Q4_K_XL.gguf mmproj = C:Usersrainlmstudiomodelspeculiar-ragdollTiel-Coder-35B-A3B-GGUF-MTPmmproj-BF16.gguf no-mmproj-offload = on c = 100000 parallel = 1 flash-attn = on cache-type-k = q8_0 cache-type-v = q8_0 load-mode = dio fit = on fit-target = 256 # MiB n-gpu-layers = 99 n-cpu-moe = 28 batch-size = 2048 ubatch-size = 512 threads = 6 prio = 2 prio-batch = 2 spec-type = draft-mtp spec-draft-n-max = 3 spec-draft-p-min = 0.75 jinja = on chat-template-file = C:UsersrainQwen-Fixed-Chat-Templateshat_template.jinja temp = 0.6 top-p = 0.95 top-k = 20 min-p = 0.0 presence-penalty = 0.0 alias = tiel-coder-35b submitted by /u/Loose_Doubt367 [link] [comments]
Related
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- 3 days benchmarking most llama.cpp flags on my weird 40gb vram laptop + tb4 egpu setup. Got +70% generation, +40% prefill, 60k more context, and filed a bug in llama around MTP. What I learned.
- Qwen3.8-Flash-Next in llama.cpp vs SGLang vs FreeToken: 35s vs 258s to first token at full context. My findings on new PRs coming to engines.
Source: r/LocalLLaMA | 2026-10-10