Gemma 3 4B IT Q4_K_M

Gemma 3 4B IT · 3.9B dense · llama.cpp · GGUF Q4_K_M · 2.49 GB · ggml-org/gemma-3-4b-it-GGUF @d097622

Generation, empty context

166 t/s

± 0.44

Generation at 16k context

156 t/s

Prompt processing

7,855 t/s

Peak VRAM

3.4 GB

during llama-bench

GPU power while generating

210 W

Energy efficiency

0.79 tok/J

Settings

llama-server -m gemma-3-4b-it-Q4_K_M.gguf --host 127.0.0.1 --port 8080 -a gemma-3-4b-it-q4_k_m-gguf/32k-q8kv --fit off -c 32768 -np 1 --cache-ram 0 -ngl 999 -fa on -ctk q8_0 -ctv q8_0 -b 2048 -ub 512 -t 6 -ncmoe 0 -lm mmap --metrics

Setting	Value
`ctx`	32768
`gpu_layers`	999
`flash_attn`	on
`cache_type_k`	q8_0
`cache_type_v`	q8_0
`batch`	2048
`ubatch`	512
`threads`	6
`n_cpu_moe`	0
`parallel`	1
`load_mode`	mmap
`cache_ram_mib`	0
`spec`	—
`reasoning_format`	—
`reasoning_budget`	—
`extra_args`	[]

Highlighted rows differ between this model's configs.

Speed

Generation vs context depth

All configs of this model; the selected one is solid.

Prompt processing vs context depth

Test	Depth	t/s	± sd	Reps	GPU W	Tok/J
pp512 llama-bench	0	7,855	574	5	—	—
pp512 llama-bench	4k	7,369	426	5	196	37.7
pp512 llama-bench	16k	6,598	332	5	211	31.2
tg128 llama-bench	0	166	0.44	5	210	0.79
tg128 llama-bench	4k	161	0.66	5	214	0.75
tg128 llama-bench	16k	156	0.60	5	222	0.70

GPU power during the run

VRAM during the run

Quality

Not measured yet: perplexity and KL-divergence against a reference quant.

Task evals

Not measured yet.

Run history

Date	Kind	Engine build	Driver	Duration	Flags
2026-09-15 18:42	speed	`llama.cpp@91f6a6cf3`	595.99.02	0.6 min