3 ms·
Yeah. I have not really tinkered much with parameter optimisation for the 35B model with MTP. Would be interested to see what you've found. I'm using the GGUF
by dofm 5mo ago
Yeah. I have not really tinkered much with parameter optimisation for the 35B model with MTP. Would be interested to see what you've found.
I'm using the GGUF too; it appears slightly faster in llama.cpp now than current LM Studio but it's not clear to me if that is down to LM Studio having a little more code overhead, older llama.cpp under the hood, or just parameter differences.
- amboo7 5mo agoTrying to recall... # 27B GGUF # Benchmark results: # - TG speed: ~5 tok/s (vs baseline ~4.5 tok/s, +10% improvement) # - PP speed: ~60 tok/s (stable across context sizes) # - With parallel=4: total throughput ~28 tok/s llama-server \ -m /Users/*/models/hf/models--unsloth--Qwen3.6-27B-GGUF/snapshots/82d411acf4a06cfb8d9b073a5211bf410bfc29bf/Qwen3.6-27B-Q6_K.gguf \ --alias "qwen3.6-27b" \ -ngl -1 \ --n-cpu-moe 0 \ -fa off \ -ctk q4_0 \ -ctv f16 \ -c 131071 \ -b 512 \ -ub 256 \ --spec-type ngram-cache \ --jinja \ --cache-ram -1 \ --parallel 4 \ --kv-unified \ --no-context-shift \ --mlock \ --slot-save-path ~/qwen_slots \ --reasoning-budget 512 \... # 27B MTP GGUF # Benchmark results (from bench_conversation.sh, ~500tok prompts + multi-turn): # Config | PP (tok/s) | TG (tok/s) | Draft accept # ---------------------------------------|------------|------------|------------- # Baseline (ngram-cache, non-MTP) | 48.0 | 5.2 | N/A # MTP --no-mmap, dn=4, fa on, ctk q4_0 | 45.7 | 6.9 | 60% # MTP --no-mmap, dn=3, fa on, ctk q4_0 | 46.3 | 7.5 | 73% ← winner MODEL="/Users/bale/models/hf/models--unsloth--Qwen3.6-27B-MTP-GGUF/snapshots/ac393bc3d23fd5a929a85e2f33c7c4fd5be02d43/Qwen3.6-27B-Q6_K.gguf" llama-server \ -m "$MODEL" \ --alias "qwen3.6-27b-mtp" \ -ngl -1 \ --n-cpu-moe 0 \ --no-mmap \ -fa on \ -ctk q4_0 \ -ctv f16 \ -c 131071 \ -b 512 \ -ub 256 \ --spec-type draft-mtp \ --spec-draft-n-max 3 \ --jinja \ --cache-ram -1 \ --parallel 1 \ --kv-unified \ --no-context-shift \ --slot-save-path ~/qwen_slots \ --reasoning-budget 512 \... # 35B GGUF # Benchmark results: # - TG speed: ~27 tok/s (vs baseline ~21 tok/s, +30% improvement) # - PP speed: ~370-350 tok/s (slight decrease with larger context) # - Parallel=4 gives best throughput at ~152 tok/s total llama-server \ -m /Users/*/models/hf/models--unsloth--Qwen3.6-35B-A3B-GGUF/snapshots/9280dd353ab587157920d5bd391ada414d84e552/Qwen3.6-35B-A3B-UD-Q6_K_XL.gguf \ --alias "qwen3.6-35b" \ -ngl -1 \ --n-cpu-moe 0 \ -fa on \ -ctk f16 \ -ctv f16 \ -c 262144 \ -b 2048 \ -ub 512 \ --spec-type ngram-cache \ --jinja \ --cache-ram -1 \ --parallel 4 \ --kv-unified \ --no-context-shift \ --mlock \ --threads 4 \ --threads-batch 8 \ --slot-save-path ~/qwen_slots \ --reasoning-budget 512 \... # 35B MTP GGUF # Benchmark results (128K context, verified 2026-05-18): # TG: 30.7 tok/s, Draft accept: 65%, no OOM at 128K MODEL="/Users/**/models/hf/models--unsloth--Qwen3.6-35B-A3B-MTP-GGUF/snapshots/e28512781649329c5b37cbf55029355a48d158d4/Qwen3.6-35B-A3B-UD-Q6_K_XL.gguf" export GGML_METAL_BF16_DISABLE=1 llama-server \ -m "$MODEL" \ --alias "qwen3.6-35b-mtp" \ -ngl -1 \ --n-cpu-moe 0 \ --no-mmap \ -fa on \ -ctk f16 \ -ctv f16 \ -c 262144 \ -b 512 \ -ub 256 \ --spec-type draft-mtp \ --spec-draft-n-max 3 \ --jinja \ --cache-ram -1 \ --parallel 1 \ --no-context-shift \ --threads 4 \ --threads-batch 8 \ --slot-save-path ~/qwen_slots \ --reasoning-budget 512 \...