Split (1)

train · 49 rows

model stringclasses 7 values	architecture stringclasses 4 values	params_b float64 11.9 79.7	quant stringclasses 4 values	size_gib float64 9.1 24.9	engine stringclasses 1 value	backend stringclasses 1 value	gpu stringclasses 1 value	vram_gb int64 32 32	test stringclasses 7 values	tokens_per_sec float64 77 16.7k	stddev float64 0.09 453	date stringdate 2026-05-28 00:00:00 2026-06-04 00:00:00
Qwen3.6-35B-A3B	MoE (3B active)	34.66	UD-Q4_K_M	20.61	llama.cpp	CUDA	RTX 5090	32	pp128	3,605.03	48.69	2026-05-28
Qwen3.6-35B-A3B	MoE (3B active)	34.66	UD-Q4_K_M	20.61	llama.cpp	CUDA	RTX 5090	32	pp512	9,239.86	63.85	2026-05-28
Qwen3.6-35B-A3B	MoE (3B active)	34.66	UD-Q4_K_M	20.61	llama.cpp	CUDA	RTX 5090	32	pp2048	9,041.04	65.96	2026-05-28
Qwen3.6-35B-A3B	MoE (3B active)	34.66	UD-Q4_K_M	20.61	llama.cpp	CUDA	RTX 5090	32	pp4096	8,760.53	53.07	2026-05-28
Qwen3.6-35B-A3B	MoE (3B active)	34.66	UD-Q4_K_M	20.61	llama.cpp	CUDA	RTX 5090	32	pp8192	8,442.99	37.16	2026-05-28
Qwen3.6-35B-A3B	MoE (3B active)	34.66	UD-Q4_K_M	20.61	llama.cpp	CUDA	RTX 5090	32	pp16384	7,713.79	15.46	2026-05-28
Qwen3.6-35B-A3B	MoE (3B active)	34.66	UD-Q4_K_M	20.61	llama.cpp	CUDA	RTX 5090	32	tg128	270.97	1.24	2026-05-28
Qwen3.6-27B	Dense	26.9	Q4_K_M	15.66	llama.cpp	CUDA	RTX 5090	32	pp128	2,972.93	322.84	2026-05-28
Qwen3.6-27B	Dense	26.9	Q4_K_M	15.66	llama.cpp	CUDA	RTX 5090	32	pp512	3,825.83	41.56	2026-05-28
Qwen3.6-27B	Dense	26.9	Q4_K_M	15.66	llama.cpp	CUDA	RTX 5090	32	pp2048	3,740.84	1.29	2026-05-28
Qwen3.6-27B	Dense	26.9	Q4_K_M	15.66	llama.cpp	CUDA	RTX 5090	32	pp4096	3,644.93	2.76	2026-05-28
Qwen3.6-27B	Dense	26.9	Q4_K_M	15.66	llama.cpp	CUDA	RTX 5090	32	pp8192	3,484.57	7.2	2026-05-28
Qwen3.6-27B	Dense	26.9	Q4_K_M	15.66	llama.cpp	CUDA	RTX 5090	32	pp16384	3,161.79	3.66	2026-05-28
Qwen3.6-27B	Dense	26.9	Q4_K_M	15.66	llama.cpp	CUDA	RTX 5090	32	tg128	77.09	0.16	2026-05-28
Nemotron-3-Nano-30B-A3B	MoE (3B active)	31.58	Q4_K_M	22.88	llama.cpp	CUDA	RTX 5090	32	pp128	4,423.05	74.78	2026-05-28
Nemotron-3-Nano-30B-A3B	MoE (3B active)	31.58	Q4_K_M	22.88	llama.cpp	CUDA	RTX 5090	32	pp512	10,674.44	108.43	2026-05-28
Nemotron-3-Nano-30B-A3B	MoE (3B active)	31.58	Q4_K_M	22.88	llama.cpp	CUDA	RTX 5090	32	pp2048	10,277.54	40.85	2026-05-28
Nemotron-3-Nano-30B-A3B	MoE (3B active)	31.58	Q4_K_M	22.88	llama.cpp	CUDA	RTX 5090	32	pp4096	9,999.48	26.46	2026-05-28
Nemotron-3-Nano-30B-A3B	MoE (3B active)	31.58	Q4_K_M	22.88	llama.cpp	CUDA	RTX 5090	32	pp8192	9,448.36	34.02	2026-05-28
Nemotron-3-Nano-30B-A3B	MoE (3B active)	31.58	Q4_K_M	22.88	llama.cpp	CUDA	RTX 5090	32	pp16384	8,558.68	16.72	2026-05-28
Nemotron-3-Nano-30B-A3B	MoE (3B active)	31.58	Q4_K_M	22.88	llama.cpp	CUDA	RTX 5090	32	tg128	363.69	1.58	2026-05-28
gpt-oss-20b	Dense	20.91	Q4_K_M	10.81	llama.cpp	CUDA	RTX 5090	32	pp128	7,220.69	67.12	2026-05-28
gpt-oss-20b	Dense	20.91	Q4_K_M	10.81	llama.cpp	CUDA	RTX 5090	32	pp512	16,749.65	148.73	2026-05-28
gpt-oss-20b	Dense	20.91	Q4_K_M	10.81	llama.cpp	CUDA	RTX 5090	32	pp2048	13,524.44	12.42	2026-05-28
gpt-oss-20b	Dense	20.91	Q4_K_M	10.81	llama.cpp	CUDA	RTX 5090	32	pp4096	11,684.53	43.99	2026-05-28
gpt-oss-20b	Dense	20.91	Q4_K_M	10.81	llama.cpp	CUDA	RTX 5090	32	pp8192	9,413.7	16.38	2026-05-28
gpt-oss-20b	Dense	20.91	Q4_K_M	10.81	llama.cpp	CUDA	RTX 5090	32	pp16384	6,677.6	14.13	2026-05-28
gpt-oss-20b	Dense	20.91	Q4_K_M	10.81	llama.cpp	CUDA	RTX 5090	32	tg128	367.9	1.18	2026-05-28
Qwen3.6-27B-MTP	Dense (MTP)	27.32	Q4_K_M	15.92	llama.cpp	CUDA	RTX 5090	32	pp128	2,972.2	321.87	2026-05-28
Qwen3.6-27B-MTP	Dense (MTP)	27.32	Q4_K_M	15.92	llama.cpp	CUDA	RTX 5090	32	pp512	3,835.77	43.26	2026-05-28
Qwen3.6-27B-MTP	Dense (MTP)	27.32	Q4_K_M	15.92	llama.cpp	CUDA	RTX 5090	32	pp2048	3,746.68	1.53	2026-05-28
Qwen3.6-27B-MTP	Dense (MTP)	27.32	Q4_K_M	15.92	llama.cpp	CUDA	RTX 5090	32	pp4096	3,655.53	9.44	2026-05-28
Qwen3.6-27B-MTP	Dense (MTP)	27.32	Q4_K_M	15.92	llama.cpp	CUDA	RTX 5090	32	pp8192	3,495.59	4.04	2026-05-28
Qwen3.6-27B-MTP	Dense (MTP)	27.32	Q4_K_M	15.92	llama.cpp	CUDA	RTX 5090	32	pp16384	3,161.77	3.81	2026-05-28
Qwen3.6-27B-MTP	Dense (MTP)	27.32	Q4_K_M	15.92	llama.cpp	CUDA	RTX 5090	32	tg128	76.99	0.09	2026-05-28
Qwen3-Coder-Next	MoE	79.67	UD-Q2_K_XL	24.92	llama.cpp	CUDA	RTX 5090	32	pp128	2,381.32	29.12	2026-05-28
Qwen3-Coder-Next	MoE	79.67	UD-Q2_K_XL	24.92	llama.cpp	CUDA	RTX 5090	32	pp512	4,447.3	39.42	2026-05-28
Qwen3-Coder-Next	MoE	79.67	UD-Q2_K_XL	24.92	llama.cpp	CUDA	RTX 5090	32	pp2048	4,420.86	35.94	2026-05-28
Qwen3-Coder-Next	MoE	79.67	UD-Q2_K_XL	24.92	llama.cpp	CUDA	RTX 5090	32	pp4096	4,380.75	11.49	2026-05-28
Qwen3-Coder-Next	MoE	79.67	UD-Q2_K_XL	24.92	llama.cpp	CUDA	RTX 5090	32	pp8192	4,250.74	14.71	2026-05-28
Qwen3-Coder-Next	MoE	79.67	UD-Q2_K_XL	24.92	llama.cpp	CUDA	RTX 5090	32	pp16384	4,042.73	18.93	2026-05-28
Qwen3-Coder-Next	MoE	79.67	UD-Q2_K_XL	24.92	llama.cpp	CUDA	RTX 5090	32	tg128	224.87	1.86	2026-05-28
Gemma 4 12B	Dense	11.91	Q6_K	9.1	llama.cpp	CUDA	RTX 5090	32	pp128	5,099.28	452.85	2026-06-04
Gemma 4 12B	Dense	11.91	Q6_K	9.1	llama.cpp	CUDA	RTX 5090	32	pp512	7,160.37	149.07	2026-06-04
Gemma 4 12B	Dense	11.91	Q6_K	9.1	llama.cpp	CUDA	RTX 5090	32	pp2048	6,788.28	10.42	2026-06-04
Gemma 4 12B	Dense	11.91	Q6_K	9.1	llama.cpp	CUDA	RTX 5090	32	pp4096	6,605.39	1.81	2026-06-04
Gemma 4 12B	Dense	11.91	Q6_K	9.1	llama.cpp	CUDA	RTX 5090	32	pp8192	6,359.06	5.49	2026-06-04
Gemma 4 12B	Dense	11.91	Q6_K	9.1	llama.cpp	CUDA	RTX 5090	32	pp16384	5,846.08	5.21	2026-06-04
Gemma 4 12B	Dense	11.91	Q6_K	9.1	llama.cpp	CUDA	RTX 5090	32	tg128	122.3	0.19	2026-06-04

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