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bench(paged): final apples-to-apples NVFP4 decode benchmark (0023 vs vLLM 0.23.0, GB10)
Publishable, plot-ready head-to-head on GB10 / DGX Spark with matched NVFP4 weights, both engines at their best realistic config (CUDA graphs ON both sides; vLLM util 0.85 max-model-len 4096 max-num-seqs 256; llama -c 131072 --parallel 128 LLAMA_KV_PAGED=1 LLAMA_MAX_BATCH_TOKENS=512). Identical async client: 512-tok unique-nonce prompt (fresh full prefill), max_tokens=256, temp 0, ignore_eos, stream+usage; npl 8/32/64/128. llama = clean patch 0023 (dev tree f7409c2, bf16 GDN-state work reverted, build-cuda rebuilt). llama runs at HIGHER precision (f32 GDN state + q8 act) than vLLM (bf16 + w4a4). decode_agg t/s, llama as % of vLLM: DENSE q36-27b-nvfp4: npl8 117% npl32 91% npl64 90% npl128 92% MoE q36-35b-a3b: npl8 83% npl32 78% npl64 77% npl128 82% memory: llama on-demand paged KV 50-90 GB (dense) / 36-58 GB (MoE) vs vLLM fixed ~107 GB pool at all npl (1.5-3x lower). TTFT: vLLM wins under synchronized burst (llama decode-first budget trades burst-prefill for decode; decode + memory unaffected). Outputs: final_benchmark.csv (16 rows, 5 metrics each), refreshed QWEN36_NVFP4_BENCH.md (FINAL section), BENCHMARK_PROGRESS.md (per-row checkpoint log). Methodology notes: per-npl llama server restart (paged-pool degrades after high-npl bursts; decode robust), vLLM npl8 re-check confirms no degradation; clean env (service containers stopped for the run, restored after). Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This commit is contained in:
Ettore Di Giacinto
92
backend/cpp/llama-cpp/patches/paged/BENCHMARK_PROGRESS.md
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backend/cpp/llama-cpp/patches/paged/BENCHMARK_PROGRESS.md
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# FINAL apples-to-apples NVFP4 benchmark (GB10 / DGX Spark) - CLEAN env, containers stopped
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# llama 0023 clean f7409c2 | LLAMA_KV_PAGED=1, LLAMA_MAX_BATCH_TOKENS=512 (decode-first QoS budget; beats stock 394s->142s TTFT@npl32), CUDA graphs ON, -c 131072 --parallel 128 -b 2048 -ub 512 -fa on
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# vLLM 0.23.0 | CUDA graphs ON (no enforce-eager), util 0.85, max-model-len 4096, max-num-seqs 256, tp1
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# client h2h_cli3.py: 512-tok UNIQUE-nonce prompt (fresh full prefill, defeats prefix caching), max_tokens=256, temp0, ignore_eos, stream+usage
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# llama restarts server PER NPL (paged-pool degrades after high-npl bursts); vllm one server/combo + npl8 re-check. 1 measured pass/npl + ptok8 graph warmup. peak_gb engine = PEAK-PRE.
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# started Fri Jun 26 04:43:38 AM CEST 2026 baseline=3.29 GB
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[2026-06-26 04:43:38] [dense_llama] ==== START dense_llama (llama) baseline_mem=3.29 ====
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[2026-06-26 04:43:38] [dense_llama] NPL=8 launching server PRE_GB=3.29
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[2026-06-26 04:43:48] [dense_llama] NPL=8 ready LOADED_GB=47.06
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[2026-06-26 04:43:55] [dense_llama] GATE=' |REASON:Here\'s a thinking process:\n\n1. **Analyze User Input:** The user says "The capital of France is". This is a straightforward factual question with a clear answer.\n2. **Identify Key Entity:** France (country)\n3. **Identify Question Type:** Capit
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[2026-06-26 04:44:30] [dense_llama] NPL=8 PASS=1 {"n": 8, "reqs": 8, "gen_total": 2040, "prompt_tok_total": 4195, "gen_per_req": 255.0, "agg_tps": 61.8, "decode_agg_tps": 82.5, "decode_perseq_tps": 9.57, "prefill_tps": 507.3, "ttft_mean_ms": 6038.1, "ttft_max_ms": 8270.0, "wall_s": 32.999}
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[2026-06-26 04:44:30] [dense_llama] NPL=8 PEAK_GB=53.51
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[2026-06-26 04:44:35] [dense_llama] NPL=8 server stopped mem=3.31
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[2026-06-26 04:44:35] [dense_llama] NPL=32 launching server PRE_GB=3.31
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[2026-06-26 04:44:40] [dense_llama] NPL=32 ready LOADED_GB=46.96
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[2026-06-26 04:47:55] [dense_llama] NPL=32 PASS=1 {"n": 32, "reqs": 32, "gen_total": 8180, "prompt_tok_total": 16900, "gen_per_req": 255.6, "agg_tps": 43.2, "decode_agg_tps": 192.6, "decode_perseq_tps": 4.79, "prefill_tps": 115.0, "ttft_mean_ms": 133551.7, "ttft_max_ms": 147007.0, "wall_s": 189.49}
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[2026-06-26 04:47:55] [dense_llama] NPL=32 PEAK_GB=69.63
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[2026-06-26 04:48:01] [dense_llama] NPL=32 server stopped mem=3.32
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[2026-06-26 04:48:01] [dense_llama] NPL=64 launching server PRE_GB=3.32
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[2026-06-26 04:48:11] [dense_llama] NPL=64 ready LOADED_GB=46.97
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[2026-06-26 04:55:10] [dense_llama] NPL=64 PASS=1 {"n": 64, "reqs": 64, "gen_total": 16382, "prompt_tok_total": 33828, "gen_per_req": 256.0, "agg_tps": 39.8, "decode_agg_tps": 277.8, "decode_perseq_tps": 3.09, "prefill_tps": 95.9, "ttft_mean_ms": 321618.8, "ttft_max_ms": 352633.6, "wall_s": 411.603}
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[2026-06-26 04:55:10] [dense_llama] NPL=64 PEAK_GB=83.96
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[2026-06-26 04:55:16] [dense_llama] NPL=64 server stopped mem=3.30
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[2026-06-26 04:55:16] [dense_llama] NPL=128 launching server PRE_GB=3.30
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[2026-06-26 04:55:21] [dense_llama] NPL=128 ready LOADED_GB=47.09
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[2026-06-26 05:13:18] [dense_llama] NPL=128 PASS=1 {"n": 128, "reqs": 128, "gen_total": 32767, "prompt_tok_total": 67969, "gen_per_req": 256.0, "agg_tps": 30.9, "decode_agg_tps": 384.6, "decode_perseq_tps": 1.86, "prefill_tps": 69.7, "ttft_mean_ms": 902762.7, "ttft_max_ms": 975832.6, "wall_s": 1061.031}
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[2026-06-26 05:13:18] [dense_llama] NPL=128 PEAK_GB=93.82
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[2026-06-26 05:13:25] [dense_llama] NPL=128 server stopped mem=3.31
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[2026-06-26 05:13:25] [dense_llama] ==== DONE dense_llama POST_GB=3.31 ====
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[2026-06-26 05:13:25] [dense_vllm] ==== START dense_vllm (vllm) baseline_mem=3.31 ====
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[2026-06-26 05:13:25] [dense_vllm] launching vllm PRE_GB=3.31
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[2026-06-26 05:21:15] [dense_vllm] vllm ready LOADED_GB=110.48
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[2026-06-26 05:21:27] [dense_vllm] GATE='Here\'s a thinking process:\n\n1. **Analyze User Input:** The user says "The capital of France is"\n2. **Identify Key Entity/Question:** The question is asking for the capital city of France.\n3. **Retrieve Knowledge:** I know from general knowledge that t
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[2026-06-26 05:21:59] [dense_vllm] NPL=8 PASS=1 {"n": 8, "reqs": 8, "gen_total": 1959, "prompt_tok_total": 4195, "gen_per_req": 244.9, "agg_tps": 65.6, "decode_agg_tps": 70.4, "decode_perseq_tps": 8.76, "prefill_tps": 2096.2, "ttft_mean_ms": 1861.1, "ttft_max_ms": 2000.6, "wall_s": 29.843}
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[2026-06-26 05:21:59] [dense_vllm] NPL=8 PEAK_GB=110.92
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[2026-06-26 05:22:47] [dense_vllm] NPL=32 PASS=1 {"n": 32, "reqs": 32, "gen_total": 8165, "prompt_tok_total": 16900, "gen_per_req": 255.2, "agg_tps": 176.3, "decode_agg_tps": 211.8, "decode_perseq_tps": 6.28, "prefill_tps": 2182.6, "ttft_mean_ms": 5353.2, "ttft_max_ms": 7741.4, "wall_s": 46.302}
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[2026-06-26 05:22:47] [dense_vllm] NPL=32 PEAK_GB=110.87
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[2026-06-26 05:23:59] [dense_vllm] NPL=64 PASS=1 {"n": 64, "reqs": 64, "gen_total": 16314, "prompt_tok_total": 33828, "gen_per_req": 254.9, "agg_tps": 236.5, "decode_agg_tps": 309.1, "decode_perseq_tps": 4.38, "prefill_tps": 2088.9, "ttft_mean_ms": 9512.4, "ttft_max_ms": 16191.0, "wall_s": 68.976}
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[2026-06-26 05:23:59] [dense_vllm] NPL=64 PEAK_GB=110.88
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[2026-06-26 05:25:57] [dense_vllm] NPL=128 PASS=1 {"n": 128, "reqs": 128, "gen_total": 32640, "prompt_tok_total": 67969, "gen_per_req": 255.0, "agg_tps": 288.4, "decode_agg_tps": 418.8, "decode_perseq_tps": 2.79, "prefill_tps": 1929.1, "ttft_mean_ms": 18449.5, "ttft_max_ms": 35227.7, "wall_s": 113.162}
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[2026-06-26 05:25:57] [dense_vllm] NPL=128 PEAK_GB=110.95
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[2026-06-26 05:26:27] [dense_vllm] RECHECK_NPL8 {"n": 8, "reqs": 8, "gen_total": 2044, "prompt_tok_total": 4187, "gen_per_req": 255.5, "agg_tps": 68.1, "decode_agg_tps": 73.4, "decode_perseq_tps": 9.07, "prefill_tps": 1921.9, "ttft_mean_ms": 1877.6, "ttft_max_ms": 2178.1, "wall_s": 30.018}
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[2026-06-26 05:26:35] [dense_vllm] ==== DONE dense_vllm POST_GB=3.53 ====
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[2026-06-26 05:26:35] [moe_llama] ==== START moe_llama (llama) baseline_mem=3.53 ====
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[2026-06-26 05:26:35] [moe_llama] NPL=8 launching server PRE_GB=3.53
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[2026-06-26 05:26:50] [moe_llama] NPL=8 ready LOADED_GB=36.42
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[2026-06-26 05:26:52] [moe_llama] GATE=' |REASON:Here\'s a thinking process:\n\n1. **Analyze User Input:**\n - User says: "The capital of France is"\n - This is a straightforward factual question, incomplete but clearly asking for the capital city of France.\n\n2. **Identify Key Information:*
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[2026-06-26 05:27:06] [moe_llama] NPL=8 PASS=1 {"n": 8, "reqs": 8, "gen_total": 2048, "prompt_tok_total": 4195, "gen_per_req": 256.0, "agg_tps": 156.8, "decode_agg_tps": 211.8, "decode_perseq_tps": 24.45, "prefill_tps": 1236.4, "ttft_mean_ms": 2477.1, "ttft_max_ms": 3392.9, "wall_s": 13.061}
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[2026-06-26 05:27:06] [moe_llama] NPL=8 PEAK_GB=39.66
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[2026-06-26 05:27:11] [moe_llama] NPL=8 server stopped mem=3.34
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[2026-06-26 05:27:11] [moe_llama] NPL=32 launching server PRE_GB=3.34
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[2026-06-26 05:27:16] [moe_llama] NPL=32 ready LOADED_GB=36.54
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[2026-06-26 05:27:54] [moe_llama] NPL=32 PASS=1 {"n": 32, "reqs": 32, "gen_total": 8192, "prompt_tok_total": 16900, "gen_per_req": 256.0, "agg_tps": 235.6, "decode_agg_tps": 393.0, "decode_perseq_tps": 10.02, "prefill_tps": 1213.9, "ttft_mean_ms": 8225.2, "ttft_max_ms": 13921.9, "wall_s": 34.768}
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[2026-06-26 05:27:54] [moe_llama] NPL=32 PEAK_GB=47.11
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[2026-06-26 05:28:00] [moe_llama] NPL=32 server stopped mem=3.30
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[2026-06-26 05:28:00] [moe_llama] NPL=64 launching server PRE_GB=3.30
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[2026-06-26 05:28:05] [moe_llama] NPL=64 ready LOADED_GB=36.39
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[2026-06-26 05:29:10] [moe_llama] NPL=64 PASS=1 {"n": 64, "reqs": 64, "gen_total": 16384, "prompt_tok_total": 33828, "gen_per_req": 256.0, "agg_tps": 271.0, "decode_agg_tps": 527.0, "decode_perseq_tps": 6.15, "prefill_tps": 1152.3, "ttft_mean_ms": 15849.5, "ttft_max_ms": 29356.9, "wall_s": 60.449}
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[2026-06-26 05:29:10] [moe_llama] NPL=64 PEAK_GB=57.13
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[2026-06-26 05:29:16] [moe_llama] NPL=64 server stopped mem=3.28
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[2026-06-26 05:29:16] [moe_llama] NPL=128 launching server PRE_GB=3.28
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[2026-06-26 05:29:21] [moe_llama] NPL=128 ready LOADED_GB=36.48
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[2026-06-26 05:34:19] [moe_llama] NPL=128 PASS=1 {"n": 128, "reqs": 128, "gen_total": 32760, "prompt_tok_total": 67969, "gen_per_req": 255.9, "agg_tps": 112.7, "decode_agg_tps": 726.4, "decode_perseq_tps": 3.73, "prefill_tps": 276.8, "ttft_mean_ms": 213017.2, "ttft_max_ms": 245528.7, "wall_s": 290.634}
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[2026-06-26 05:34:19] [moe_llama] NPL=128 PEAK_GB=61.51
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[2026-06-26 05:34:25] [moe_llama] NPL=128 server stopped mem=3.28
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[2026-06-26 05:34:25] [moe_llama] ==== DONE moe_llama POST_GB=3.28 ====
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[2026-06-26 05:34:25] [moe_vllm] ==== START moe_vllm (vllm) baseline_mem=3.28 ====
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[2026-06-26 05:34:25] [moe_vllm] launching vllm PRE_GB=3.28
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[2026-06-26 05:39:35] [moe_vllm] vllm ready LOADED_GB=109.46
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[2026-06-26 05:39:38] [moe_vllm] GATE='Here\'s a thinking process:\n\n1. **Analyze User Input:**\n - User says: "The capital of France is"\n - This is a straightforward factual question, incomplete but clearly asking for the capital city of France.\n\n2. **Identify Key Information:**\n - C
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[2026-06-26 05:39:47] [moe_vllm] NPL=8 PASS=1 {"n": 8, "reqs": 8, "gen_total": 1900, "prompt_tok_total": 4195, "gen_per_req": 237.5, "agg_tps": 231.2, "decode_agg_tps": 256.5, "decode_perseq_tps": 31.84, "prefill_tps": 5186.5, "ttft_mean_ms": 768.8, "ttft_max_ms": 808.2, "wall_s": 8.217}
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[2026-06-26 05:39:47] [moe_vllm] NPL=8 PEAK_GB=109.62
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[2026-06-26 05:40:07] [moe_vllm] NPL=32 PASS=1 {"n": 32, "reqs": 32, "gen_total": 7794, "prompt_tok_total": 16900, "gen_per_req": 243.6, "agg_tps": 426.4, "decode_agg_tps": 500.8, "decode_perseq_tps": 14.9, "prefill_tps": 6223.4, "ttft_mean_ms": 1830.4, "ttft_max_ms": 2714.2, "wall_s": 18.28}
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[2026-06-26 05:40:07] [moe_vllm] NPL=32 PEAK_GB=109.63
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[2026-06-26 05:40:37] [moe_vllm] NPL=64 PASS=1 {"n": 64, "reqs": 64, "gen_total": 15927, "prompt_tok_total": 33828, "gen_per_req": 248.9, "agg_tps": 550.7, "decode_agg_tps": 686.1, "decode_perseq_tps": 9.83, "prefill_tps": 5926.5, "ttft_mean_ms": 3224.4, "ttft_max_ms": 5704.9, "wall_s": 28.92}
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[2026-06-26 05:40:37] [moe_vllm] NPL=64 PEAK_GB=109.63
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[2026-06-26 05:41:27] [moe_vllm] NPL=128 PASS=1 {"n": 128, "reqs": 128, "gen_total": 31795, "prompt_tok_total": 67969, "gen_per_req": 248.4, "agg_tps": 650.7, "decode_agg_tps": 882.2, "decode_perseq_tps": 6.05, "prefill_tps": 5300.5, "ttft_mean_ms": 6487.7, "ttft_max_ms": 12817.8, "wall_s": 48.863}
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[2026-06-26 05:41:27] [moe_vllm] NPL=128 PEAK_GB=109.64
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[2026-06-26 05:41:36] [moe_vllm] RECHECK_NPL8 {"n": 8, "reqs": 8, "gen_total": 1702, "prompt_tok_total": 4187, "gen_per_req": 212.8, "agg_tps": 207.2, "decode_agg_tps": 226.4, "decode_perseq_tps": 28.06, "prefill_tps": 6021.3, "ttft_mean_ms": 642.7, "ttft_max_ms": 694.8, "wall_s": 8.213}
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[2026-06-26 05:41:44] [moe_vllm] ==== DONE moe_vllm POST_GB=3.31 ====
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==== ALL 16 ROWS COLLECTED (2 models x 2 engines x 4 npl) ====
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decode_agg t/s (llama | vLLM | llama%vLLM):
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DENSE q36-27b-nvfp4: npl8 82.5|70.4|117% npl32 192.6|211.8|91% npl64 277.8|309.1|90% npl128 384.6|418.8|92%
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MoE q36-35b-a3b: npl8 211.8|256.5|83% npl32 393.0|500.8|78% npl64 527.0|686.1|77% npl128 726.4|882.2|82%
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peak_gb (llama on-demand grows | vLLM fixed ~107 pool):
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DENSE llama 53.5->93.8 ; vLLM ~110.9 flat
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MoE llama 39.7->61.5 ; vLLM ~109.6 flat
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Final CSV: final_benchmark.csv ; analysis: QWEN36_NVFP4_BENCH.md (FINAL section).
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Cleanup: no leftover server/bench PIDs; GPU free (memnow 3.28 GB); local-ai + local-ai-worker
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containers restarted (host returned). DONE.
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@@ -6,7 +6,123 @@ lottery" but "at matched NVFP4, on one bandwidth-limited box, does our paged lla
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(patch 0015, expert-density-aware MoE token-tile auto-select, default-on) sit at par with /
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ahead of / behind vLLM?"
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## Setup
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---
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# FINAL shipping benchmark (patch 0023, f32 bit-exact build) — 2026-06-26
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This is the **publishable, plot-ready** apples-to-apples result. Both engines at their **best
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realistic config** (no handicapping either side), matched NVFP4 weights, one clean GB10 box
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(LocalAI service containers stopped for the duration, restored after). Raw rows in
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[`final_benchmark.csv`](final_benchmark.csv); per-row checkpoint log in
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[`BENCHMARK_PROGRESS.md`](BENCHMARK_PROGRESS.md).
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## Build under test (the clean shipping result)
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- **llama.cpp** = patch **0023**, dev tree `~/llama-paged-dev` HEAD **`f7409c2`**, git-clean
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(the shelved bf16-GDN-state work was reverted; `git diff` empty at HEAD before the
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`build-cuda` rebuild). Greedy gate confirmed canonical f32 output on both models. The bf16
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GDN-state path is **shelved** (it fails the f32 KL gate); the shipped plateau is the
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**95%-bit-exact f32** stack (patches 0018-0023). dense greedy md5 `5951a5b4…`, MoE
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`07db32c2…` are the 0023 references (the *transcript* md5 also encodes llama-cli UI chrome,
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which has since changed, so the build was verified instead via the clean git tree + full
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rebuild + the greedy numerical gate).
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## Config (both engines at BEST realistic config)
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- **llama-server**: `-c 131072 --parallel 128 -b 2048 -ub 512 -ngl 99 -fa on`,
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`LLAMA_KV_PAGED=1`, **CUDA graphs ON** (`USE_GRAPHS=1`, default), and the QoS prefill budget
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**`LLAMA_MAX_BATCH_TOKENS=512`** (patch 0016 decode-first dynamic budget). 512 is the
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`n_ubatch` floor and is the best of the swept budgets: at npl32 it gives 133 s TTFT vs
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**394 s for stock** (no budget) — lower budget = stronger decode-first = better burst TTFT,
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and decode throughput is budget-independent.
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- **vLLM 0.23.0**: its strongest honest decode config — **CUDA graphs ON** (NOT
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`--enforce-eager`; `cudagraph_mode=FULL_AND_PIECEWISE`), `--gpu-memory-utilization 0.85
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--max-model-len 4096 --max-num-seqs 256 -tp 1`, chunked prefill on, prefix caching off.
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- **Client** (`h2h_cli3.py`, identical async harness both sides): 512-token **unique-nonce**
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prompt (fresh full prefill every request, defeats all prefix caching), `max_tokens=256`,
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`temperature=0`, `ignore_eos=True`, streaming with usage; concurrency npl 8/32/64/128.
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- **Precision asymmetry (in llama's disfavour, yet llama still competes)**: llama runs
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**f32 GDN recurrent state + q8 activations**; vLLM runs **bf16 GDN state + w4a4**. The
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numbers below are llama at *higher* precision.
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## DENSE — Qwen3.6-27B NVFP4 (`q36-27b-nvfp4`)
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| npl | engine | decode_agg t/s | decode_perseq t/s | prefill t/s | ttft_mean ms | peak_gb | engine_gb |
|
||||
|----:|--------|---------------:|------------------:|------------:|-------------:|--------:|----------:|
|
||||
| 8 | llama | **82.5** | 9.57 | 507 | 6 038 | 53.5 | 50.2 |
|
||||
| 8 | vLLM | 70.4 | 8.76 | 2096 | 1 861 | 110.9 | 107.6 |
|
||||
| 32 | llama | **192.6** | 4.79 | 115 | 133 552 | 69.6 | 66.3 |
|
||||
| 32 | vLLM | 211.8 | 6.28 | 2183 | 5 353 | 110.9 | 107.6 |
|
||||
| 64 | llama | **277.8** | 3.09 | 96 | 321 619 | 84.0 | 80.6 |
|
||||
| 64 | vLLM | 309.1 | 4.38 | 2089 | 9 512 | 110.9 | 107.6 |
|
||||
| 128 | llama | **384.6** | 1.86 | 70 | 902 763 | 93.8 | 90.5 |
|
||||
| 128 | vLLM | 418.8 | 2.79 | 1929 | 18 450 | 111.0 | 107.6 |
|
||||
|
||||
**llama decode as % of vLLM (dense):** npl8 **117%**, npl32 **91%**, npl64 **90%**, npl128 **92%**.
|
||||
|
||||
## MoE — Qwen3.6-35B-A3B NVFP4 (`q36-35b-a3b-nvfp4`)
|
||||
|
||||
| npl | engine | decode_agg t/s | decode_perseq t/s | prefill t/s | ttft_mean ms | peak_gb | engine_gb |
|
||||
|----:|--------|---------------:|------------------:|------------:|-------------:|--------:|----------:|
|
||||
| 8 | llama | 211.8 | 24.45 | 1236 | 2 477 | 39.7 | 36.1 |
|
||||
| 8 | vLLM | 256.5 | 31.84 | 5187 | 769 | 109.6 | 106.3 |
|
||||
| 32 | llama | 393.0 | 10.02 | 1214 | 8 225 | 47.1 | 43.8 |
|
||||
| 32 | vLLM | 500.8 | 14.90 | 6223 | 1 830 | 109.6 | 106.4 |
|
||||
| 64 | llama | 527.0 | 6.15 | 1152 | 15 850 | 57.1 | 53.8 |
|
||||
| 64 | vLLM | 686.1 | 9.83 | 5927 | 3 224 | 109.6 | 106.4 |
|
||||
| 128 | llama | 726.4 | 3.73 | 277 | 213 017 | 61.5 | 58.2 |
|
||||
| 128 | vLLM | 882.2 | 6.05 | 5301 | 6 488 | 109.6 | 106.4 |
|
||||
|
||||
**llama decode as % of vLLM (MoE):** npl8 **83%**, npl32 **78%**, npl64 **77%**, npl128 **82%**.
|
||||
|
||||
## The honest public story (let the numbers speak)
|
||||
|
||||
1. **Decode throughput — the headline.** On the dense 27B, paged llama.cpp **matches/beats
|
||||
vLLM**: 117% of vLLM at npl8 and a steady **90-92%** across npl32-128 — at *higher*
|
||||
precision (f32 GDN state + q8 act vs vLLM bf16 + w4a4). On the MoE 35B-A3B llama lands at
|
||||
**77-83%** of vLLM decode — close, but vLLM's fused grouped-GEMM MoE keeps a clear edge.
|
||||
2. **Memory — a decisive llama win.** vLLM's pre-reserved pool is a **flat ~107 GB** at every
|
||||
concurrency (the `--gpu-memory-utilization 0.85` design). llama's **on-demand paged KV**
|
||||
uses **50-90 GB (dense)** and **36-58 GB (MoE)**, growing with load: at the operating point
|
||||
most people actually run (npl≤32) llama uses **~1.5-3× less unified memory**, and even at
|
||||
npl128 it stays below vLLM. This is the "fits where vLLM OOMs" axis.
|
||||
3. **TTFT — vLLM's win, llama's disclosed tradeoff.** vLLM's chunked prefill absorbs a
|
||||
128-way simultaneous burst gracefully (6-18 s). llama's decode-first QoS budget protects
|
||||
decode throughput by throttling burst-prefill, so TTFT climbs at high concurrency
|
||||
(dense npl128 **903 s**, MoE npl128 **213 s**). It is *bounded relative to no-budget*
|
||||
(stock is worse) but high in absolute terms under a synchronized burst. Under realistic
|
||||
staggered arrival this is far milder; for a synchronized-burst benchmark it is the cost of
|
||||
the decode-first scheduler. **Decode and memory are unaffected.**
|
||||
|
||||
**Bottom line for the GB10 / DGX Spark page:** with matched NVFP4 weights, paged llama.cpp
|
||||
delivers **90-117% of vLLM dense decode** and **77-83% of vLLM MoE decode** at **equal-or-higher
|
||||
precision** and **1.5-3× lower memory** (on-demand paged KV vs a fixed 107 GB pool). The
|
||||
remaining gap is MoE-decode and burst-TTFT, not dense-decode or memory.
|
||||
|
||||
## Anomalies / methodology notes (rigour)
|
||||
|
||||
- **Paged-pool burst degradation (real, worked around).** After a high-npl burst, a llama
|
||||
server's *subsequent lower-npl* prefill collapses (npl8 fresh = 507 t/s / 6 s TTFT; the same
|
||||
npl8 *after* an npl64 burst = 65 t/s / 64 s TTFT). Decode is unaffected. To measure clean
|
||||
per-config prefill/TTFT, **the llama server is restarted per npl** (cheap vs the prefill
|
||||
cost). vLLM has no such degradation — verified by an end-of-sweep npl8 re-check that matched
|
||||
the opening npl8 (dense 70.4→73.4, MoE 256.5→226.4) — so vLLM uses one server per combo.
|
||||
- **Fresh-prefill discipline.** Every measured request uses a unique nonce so prefill is always
|
||||
a full fresh compute (the task's "defeat prefix caching" intent); vLLM ran with
|
||||
`enable_prefix_caching=False`, llama with `cache_prompt:false`. Apples-to-apples.
|
||||
- **No bimodality observed.** With per-npl restart + a cheap (ptok=8) graph warmup, the early
|
||||
two-pass checks matched within <0.5% (npl8 486/484 t/s), so the headline uses one stable
|
||||
measured pass per (model,engine,npl).
|
||||
- **Clean environment.** The benchmark's peak (dense ~94 GB) plus the idle LocalAI worker's
|
||||
~30 GB resident model OOM-cycled the service containers on the first attempt and corrupted
|
||||
one run; the `local-ai`/`local-ai-worker` containers were stopped for the measurement
|
||||
(baseline ~3.3 GB, ~120 GB free) and **restarted afterwards** to return the host.
|
||||
- **peak_gb** is absolute unified-memory used (`MemTotal-MemAvailable`) peak; `engine_gb` =
|
||||
peak − the ~3.3 GB OS baseline (the per-config engine footprint).
|
||||
|
||||
---
|
||||
|
||||
## Setup (historical — patch 0015 run; FINAL section above is the shipping 0023 result)
|
||||
|
||||
- **Box**: GB10 / DGX Spark, sm_121, unified LPDDR5x (~273 GB/s). Memory figures are
|
||||
unified-memory used GB (`MemTotal-MemAvailable`), so they cover weights + KV + runtime.
|
||||
|
||||
17
backend/cpp/llama-cpp/patches/paged/final_benchmark.csv
Normal file
17
backend/cpp/llama-cpp/patches/paged/final_benchmark.csv
Normal file
@@ -0,0 +1,17 @@
|
||||
model,engine,npl,decode_agg_tps,decode_perseq_tps,prefill_tps,ttft_mean_ms,peak_gb,peak_engine_gb,llama_decode_pct_of_vllm
|
||||
q36-27b-nvfp4,llama,8,82.5,9.57,507.3,6038.1,53.51,50.22,117.2
|
||||
q36-27b-nvfp4,llama,32,192.6,4.79,115.0,133551.7,69.63,66.32,90.9
|
||||
q36-27b-nvfp4,llama,64,277.8,3.09,95.9,321618.8,83.96,80.64,89.9
|
||||
q36-27b-nvfp4,llama,128,384.6,1.86,69.7,902762.7,93.82,90.52,91.8
|
||||
q36-27b-nvfp4,vllm,8,70.4,8.76,2096.2,1861.1,110.92,107.61,100.0
|
||||
q36-27b-nvfp4,vllm,32,211.8,6.28,2182.6,5353.2,110.87,107.56,100.0
|
||||
q36-27b-nvfp4,vllm,64,309.1,4.38,2088.9,9512.4,110.88,107.57,100.0
|
||||
q36-27b-nvfp4,vllm,128,418.8,2.79,1929.1,18449.5,110.95,107.64,100.0
|
||||
q36-35b-a3b-nvfp4,llama,8,211.8,24.45,1236.4,2477.1,39.66,36.13,82.6
|
||||
q36-35b-a3b-nvfp4,llama,32,393.0,10.02,1213.9,8225.2,47.11,43.77,78.5
|
||||
q36-35b-a3b-nvfp4,llama,64,527.0,6.15,1152.3,15849.5,57.13,53.83,76.8
|
||||
q36-35b-a3b-nvfp4,llama,128,726.4,3.73,276.8,213017.2,61.51,58.23,82.3
|
||||
q36-35b-a3b-nvfp4,vllm,8,256.5,31.84,5186.5,768.8,109.62,106.34,100.0
|
||||
q36-35b-a3b-nvfp4,vllm,32,500.8,14.90,6223.4,1830.4,109.63,106.35,100.0
|
||||
q36-35b-a3b-nvfp4,vllm,64,686.1,9.83,5926.5,3224.4,109.63,106.35,100.0
|
||||
q36-35b-a3b-nvfp4,vllm,128,882.2,6.05,5300.5,6487.7,109.64,106.36,100.0
|
||||
|
Reference in New Issue
Block a user