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Put two chips, runtimes, or runtime versions side by side. Everything else is held fixed or called out, so a ratio is worth exactly what the matched runs say.

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Runs compared: 524
Like-for-like pairs: 14
Runtimes available: 2

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Side A

Side B

Model

Chip

Quantisation A

Quantisation B

Backend

Prefill size

Decode size

Cooldown

375 runs vs 149 runs · 14 like-for-like pairs

Held fixedPrefill: PP512Decode: TG128

These figures mix different models. Pick a model for a like-for-like comparison.
The sides differ in conditioning, decode workload, harness schema. Ratios may reflect benchmark protocol rather than the runtime.

Runtime comparison

BaseRT vs llama.cpp

Ratios read side A relative to side B. Geometric mean over 14 like-for-like pairs.

Decode: 1.15×+14.6%
Prefill: 1.21×+21.5%

Side A

BaseRT

375 runs

7 contributors

Latest 20 Sep 2026

Decode · TG128: 91.6tok/s median
best 2,068.0 · worst 7.5
Prefill · PP512: 2,028tok/s median
best 190,107 · worst 80

Models: gemma-3-1b-it, gemma-3-1b-it-cuda-q4mix, gemma-3-1b-it-cuda-q8, gemma-3-1b-it-Q4, gemma-3-1b-it-Q8, gemma-4-26B-A4B-it, gemma-4-26B-A4B-it-cuda-q4mix, gemma-4-26B-A4B-it-cuda-q8, gemma-4-26B-A4B-it-Q4, gemma-4-26B-A4B-it-Q8, gemma-4-E2B-it, gemma-4-E2B-it-cuda-q4mix, gemma-4-E2B-it-cuda-q8, gemma-4-E2B-it-Q4, gemma-4-E2B-it-Q8, gemma-4-E4B-it, gemma-4-E4B-it-Q4, gemma-4-E4B-it-Q8, gpt-oss-120b, gpt-oss-120b-MXFP4, gpt-oss-120b-Q4, gpt-oss-120b-Q8, gpt-oss-20b, gpt-oss-20b-MXFP4, gpt-oss-20b-Q4, gpt-oss-20b-Q8, Llama-3.1-8B-Instruct, Llama-3.1-8B-Instruct-Q4, Llama-3.1-8B-Instruct-Q8, Llama-3.2-1B-Instruct, Llama-3.2-1B-Instruct-cuda-q4mix, Llama-3.2-1B-Instruct-cuda-q8, Llama-3.2-1B-Instruct-Q4, Llama-3.2-1B-Instruct-Q8, Llama-3.2-3B-Instruct, Llama-3.2-3B-Instruct-cuda-q4mix, Llama-3.2-3B-Instruct-cuda-q8, Llama-3.2-3B-Instruct-Q4, Llama-3.2-3B-Instruct-Q8, Mistral-7B-Instruct-v0.3, Mistral-7B-Instruct-v0.3-Q4, Mistral-7B-Instruct-v0.3-Q8, Muse-Glimmer-30B, muse-glimmer-30B-kquant-17gb, muse-glimmer-30B-kquant-dynamic, NVIDIA-Nemotron-3-Nano-30B-A3B, NVIDIA-Nemotron-3-Nano-30B-A3B-Q4, NVIDIA-Nemotron-3-Nano-30B-A3B-Q8, Ornith-1.5-9B, Qwen3-0.6B, Qwen3-0.6B-cuda-q4, Qwen3-0.6B-cuda-q4mix, Qwen3-0.6B-cuda-q8, Qwen3-0.6B-Q4, Qwen3-0.6B-Q8, Qwen3-1.7B, Qwen3-1.7B-Q4, Qwen3-1.7B-Q8, Qwen3-30B-A3B-Instruct-2507, Qwen3-30B-A3B-Instruct-2507-cuda-q4mix, Qwen3-30B-A3B-Instruct-2507-cuda-q8, Qwen3-30B-A3B-Instruct-2507-Q4, Qwen3-30B-A3B-Thinking-2507, Qwen3-30B-A3B-Thinking-2507-Q4, Qwen3-30B-A3B-Thinking-2507-Q8, Qwen3-4B, Qwen3-4B-Instruct-2507, Qwen3-4B-Instruct-2507-Q4, Qwen3-4B-Instruct-2507-Q8, Qwen3-4B-Q4, Qwen3-4B-Q8, Qwen3-4B-Thinking-2507, Qwen3-4B-Thinking-2507-Q4, Qwen3-4B-Thinking-2507-Q8, Qwen3-8B, Qwen3-8B-base-q2, Qwen3-8B-base-q3, Qwen3-8B-base-q5, Qwen3-8B-base-q6, Qwen3-8B-Q4, Qwen3-8B-Q8, Qwen3.5-122B-A10B-Q4, Qwen3.5-2B, Qwen3.5-2B-Base, Qwen3.5-2B-Base-Q4, Qwen3.5-2B-Base-Q8, Qwen3.5-2B-cuda-q4mix, Qwen3.5-2B-cuda-q8, Qwen3.5-2B-Q4, Qwen3.5-2B-Q8, Qwen3.5-35B-A3B, Qwen3.5-35B-A3B-cuda-q4mix, Qwen3.5-35B-A3B-cuda-q8, Qwen3.5-35B-A3B-Q4, Qwen3.5-35B-A3B-Q8, Qwen3.6-27B, Qwen3.6-27B-cuda-q4mix, Qwen3.6-27B-cuda-q8, Qwen3.6-27B-Q4, Qwen3.6-27B-Q8, Qwen3.6-35B-A3B, Qwen3.6-35B-A3B-cuda-q4mix, Qwen3.6-35B-A3B-cuda-q8, Qwen3.6-35B-A3B-Q4, Qwen3.6-35B-A3B-Q8, Qwen3.8-27B, Qwen3.8-27B-Q4, Qwen3.8-27B-Q4-mtp, Qwen3.8-27B-Q8, tinystories-lay8-hs512-hd8-33M
Chips: Apple M1 Max, Apple M1 Pro, Apple M3 Ultra, Apple M4, Apple M4 Max, Apple M4 Pro, Apple M5, Apple M5 Max, Apple M5 Pro, NVIDIA GB10
Versions: BaseRT 0.2.4, BaseRT 0.2.5, BaseRT 0.2.6
Quantisations: mxfp4, passthrough_gguf, Q2, Q3, Q4, Q5, Q6, Q8
Backends: CUDA, Metal
Cooldown: off, on
Conditioning: idle_reset_then_warm, warmup_only
Decode workload: TG128, TG128 @ 1 ctx
Harness schema: basert-benchmark-harness/1

Side B

llama.cpp

149 runs

7 contributors

Latest 17 Sep 2026

Decode · TG128: 95.6tok/s median
best 1,443.3 · worst 11.9
Prefill · PP512: 2,643tok/s median
best 124,181 · worst 78

Models: Gemma-4 12B IT (smart Q4_0, QAT-lossless), Gemma-4 26B-A4B IT (smart Q4_0, QAT-lossless), Gemma-4-E4B-It, Glm-4.6V-Flash, Gpt-Oss-20B, Llama 3.2 3B Instruct, Llama-3.1-8B-Instruct, Llama-3.2-3B-Instruct, Meta Llama 3.1 8B Instruct, ministral-8B-Instruct-2512, Models Qwen Qwen3 0.6B, Ornith-1.5-9B, Qwen 0.6b Coder, Qwen2.5 Coder 1.5B Instruct GGUF, Qwen3 0.6B Instruct, Qwen3-0.6B, Qwen3-30B-A3B-Instruct-2507, Qwen3-4B, Qwen3-4B-Instruct-2507, Qwen3-8B, Qwen3.5-4B, Qwen3.6-27B, Qwen3.6-35B-A3B, Qwen3.8-27B, Tinystories Lay8 Hs512 Hd8 33M
Chips: AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XT (RADV NAVI31), AMD Ryzen 5 7600 6-Core Processor, Apple M1 Pro, Apple M4 Max, Apple M4 Pro, Apple M5 Max, Apple M5 Pro, NVIDIA GeForce RTX 4060 Laptop GPU, NVIDIA H100 80GB HBM3 × 8, Tesla T10/Tesla T10/Tesla T10/Tesla T10
Versions: llama.cpp b1 (e64c0ea), llama.cpp b10360 (48d22e295), llama.cpp b10809 (5266f24da), llama.cpp b10894 (d344123fe), llama.cpp b10901 (28ff09582), llama.cpp b10902 (df03399b8), llama.cpp b10955 (2f539596c), llama.cpp b9650 (d8a3f523c), llama.cpp b9960 (a935fbffe)
Quantisations: BF16, F16, Q2_K, Q3_K_M, Q4_0, Q4_1, Q4_K_M, Q5_K_M, Q6_K, Q8_0
Backends: BLAS + Metal, CPU, CUDA, ROCm, Vulkan
Cooldown: off, on
Conditioning: idle_reset_before_workload_process, runtime_native_warmup
Decode workload: TG128
Harness schema: computearena-measurements/1

What differs besides the runtime

Facet	BaseRT	llama.cpp
Model	gemma-3-1b-it, gemma-3-1b-it-cuda-q4mix, gemma-3-1b-it-cuda-q8, gemma-3-1b-it-Q4, gemma-3-1b-it-Q8, gemma-4-26B-A4B-it, gemma-4-26B-A4B-it-cuda-q4mix, gemma-4-26B-A4B-it-cuda-q8, gemma-4-26B-A4B-it-Q4, gemma-4-26B-A4B-it-Q8, gemma-4-E2B-it, gemma-4-E2B-it-cuda-q4mix, gemma-4-E2B-it-cuda-q8, gemma-4-E2B-it-Q4, gemma-4-E2B-it-Q8, gemma-4-E4B-it, gemma-4-E4B-it-Q4, gemma-4-E4B-it-Q8, gpt-oss-120b, gpt-oss-120b-MXFP4, gpt-oss-120b-Q4, gpt-oss-120b-Q8, gpt-oss-20b, gpt-oss-20b-MXFP4, gpt-oss-20b-Q4, gpt-oss-20b-Q8, Llama-3.1-8B-Instruct, Llama-3.1-8B-Instruct-Q4, Llama-3.1-8B-Instruct-Q8, Llama-3.2-1B-Instruct, Llama-3.2-1B-Instruct-cuda-q4mix, Llama-3.2-1B-Instruct-cuda-q8, Llama-3.2-1B-Instruct-Q4, Llama-3.2-1B-Instruct-Q8, Llama-3.2-3B-Instruct, Llama-3.2-3B-Instruct-cuda-q4mix, Llama-3.2-3B-Instruct-cuda-q8, Llama-3.2-3B-Instruct-Q4, Llama-3.2-3B-Instruct-Q8, Mistral-7B-Instruct-v0.3, Mistral-7B-Instruct-v0.3-Q4, Mistral-7B-Instruct-v0.3-Q8, Muse-Glimmer-30B, muse-glimmer-30B-kquant-17gb, muse-glimmer-30B-kquant-dynamic, NVIDIA-Nemotron-3-Nano-30B-A3B, NVIDIA-Nemotron-3-Nano-30B-A3B-Q4, NVIDIA-Nemotron-3-Nano-30B-A3B-Q8, Ornith-1.5-9B, Qwen3-0.6B, Qwen3-0.6B-cuda-q4, Qwen3-0.6B-cuda-q4mix, Qwen3-0.6B-cuda-q8, Qwen3-0.6B-Q4, Qwen3-0.6B-Q8, Qwen3-1.7B, Qwen3-1.7B-Q4, Qwen3-1.7B-Q8, Qwen3-30B-A3B-Instruct-2507, Qwen3-30B-A3B-Instruct-2507-cuda-q4mix, Qwen3-30B-A3B-Instruct-2507-cuda-q8, Qwen3-30B-A3B-Instruct-2507-Q4, Qwen3-30B-A3B-Thinking-2507, Qwen3-30B-A3B-Thinking-2507-Q4, Qwen3-30B-A3B-Thinking-2507-Q8, Qwen3-4B, Qwen3-4B-Instruct-2507, Qwen3-4B-Instruct-2507-Q4, Qwen3-4B-Instruct-2507-Q8, Qwen3-4B-Q4, Qwen3-4B-Q8, Qwen3-4B-Thinking-2507, Qwen3-4B-Thinking-2507-Q4, Qwen3-4B-Thinking-2507-Q8, Qwen3-8B, Qwen3-8B-base-q2, Qwen3-8B-base-q3, Qwen3-8B-base-q5, Qwen3-8B-base-q6, Qwen3-8B-Q4, Qwen3-8B-Q8, Qwen3.5-122B-A10B-Q4, Qwen3.5-2B, Qwen3.5-2B-Base, Qwen3.5-2B-Base-Q4, Qwen3.5-2B-Base-Q8, Qwen3.5-2B-cuda-q4mix, Qwen3.5-2B-cuda-q8, Qwen3.5-2B-Q4, Qwen3.5-2B-Q8, Qwen3.5-35B-A3B, Qwen3.5-35B-A3B-cuda-q4mix, Qwen3.5-35B-A3B-cuda-q8, Qwen3.5-35B-A3B-Q4, Qwen3.5-35B-A3B-Q8, Qwen3.6-27B, Qwen3.6-27B-cuda-q4mix, Qwen3.6-27B-cuda-q8, Qwen3.6-27B-Q4, Qwen3.6-27B-Q8, Qwen3.6-35B-A3B, Qwen3.6-35B-A3B-cuda-q4mix, Qwen3.6-35B-A3B-cuda-q8, Qwen3.6-35B-A3B-Q4, Qwen3.6-35B-A3B-Q8, Qwen3.8-27B, Qwen3.8-27B-Q4, Qwen3.8-27B-Q4-mtp, Qwen3.8-27B-Q8, tinystories-lay8-hs512-hd8-33M	Gemma-4 12B IT (smart Q4_0, QAT-lossless), Gemma-4 26B-A4B IT (smart Q4_0, QAT-lossless), Gemma-4-E4B-It, Glm-4.6V-Flash, Gpt-Oss-20B, Llama 3.2 3B Instruct, Llama-3.1-8B-Instruct, Llama-3.2-3B-Instruct, Meta Llama 3.1 8B Instruct, ministral-8B-Instruct-2512, Models Qwen Qwen3 0.6B, Ornith-1.5-9B, Qwen 0.6b Coder, Qwen2.5 Coder 1.5B Instruct GGUF, Qwen3 0.6B Instruct, Qwen3-0.6B, Qwen3-30B-A3B-Instruct-2507, Qwen3-4B, Qwen3-4B-Instruct-2507, Qwen3-8B, Qwen3.5-4B, Qwen3.6-27B, Qwen3.6-35B-A3B, Qwen3.8-27B, Tinystories Lay8 Hs512 Hd8 33M
Chip	Apple M1 Max, Apple M1 Pro, Apple M3 Ultra, Apple M4, Apple M4 Max, Apple M4 Pro, Apple M5, Apple M5 Max, Apple M5 Pro, NVIDIA GB10	AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XT (RADV NAVI31), AMD Ryzen 5 7600 6-Core Processor, Apple M1 Pro, Apple M4 Max, Apple M4 Pro, Apple M5 Max, Apple M5 Pro, NVIDIA GeForce RTX 4060 Laptop GPU, NVIDIA H100 80GB HBM3 × 8, Tesla T10/Tesla T10/Tesla T10/Tesla T10
Backend	CUDA, Metal	BLAS + Metal, CPU, CUDA, ROCm, Vulkan
Conditioning	idle_reset_then_warm, warmup_only	idle_reset_before_workload_process, runtime_native_warmup
Decode workload	TG128, TG128 @ 1 ctx	TG128
Harness schema	basert-benchmark-harness/1	computearena-measurements/1

Like-for-like pairs

Each row is a configuration present on both sides. Values are per-cell medians; ratios read BaseRT relative to llama.cpp.

Configuration	Decode A	Decode B	Ratio	Prefill A	Prefill B	Ratio	Runs A / B
Qwen3-8B Apple M5 Pro	59.7	49.9	1.20×	1,755	1,416	1.24×	13 / 14
Qwen3-0.6B Apple M5 Pro	415.8	357.2	1.16×	20,451	14,530	1.41×	6 / 4
Llama-3.1-8B-Instruct Apple M5 Pro	48.8	55.5	0.88×	1,784	1,424	1.25×	4 / 5
Llama-3.2-3B-Instruct Apple M5 Pro	94.6	115.2	0.82×	4,297	3,318	1.30×	5 / 3
Qwen3-30B-A3B-Instruct-2507 Apple M5 Pro	98.1	95.1	1.03×	3,493	1,769	1.97×	2 / 6
gemma-4-E4B-it Apple M5 Pro	66.6	69.4	0.96×	4,563	2,263	2.02×	4 / 3
Qwen3-4B-Instruct-2507 Apple M5 Pro	76.9	92.6	0.83×	3,379	2,568	1.32×	4 / 3
gpt-oss-20b Apple M5 Pro	106.9	81.5	1.31×	1,110	1,851	0.60×	4 / 2
Qwen3.6-27B Apple M5 Pro	13.3	14.9	0.90×	360	375	0.96×	2 / 4
Qwen3-0.6B Apple M5 Max	698.5	409.0	1.71×	33,088	24,674	1.34×	3 / 2
Qwen3-4B Apple M5 Pro	103.9	93.6	1.11×	3,384	2,705	1.25×	3 / 1
Qwen3.6-35B-A3B Apple M5 Pro	113.2	61.5	1.84×	1,275	1,673	0.76×	1 / 3
Qwen3.8-27B Apple M4 Max	31.6	22.9	1.38×	222	243	0.91×	1 / 1
tinystories-lay8-hs512-hd8-33M Apple M5 Pro	2,068.0	1,443.3	1.43×	190,107	124,181	1.53×	1 / 1

Side A · BaseRT

Top 25 of 375 runs by decode throughput.

Model / format	Chip / backend	Decode	Prefill	Contributor	Date	Report
ivnle/tinystories-lay8-hs512-hd8-33M BaseRT 0.2.4Q4	Apple M5 Pro Metal	2,068.0 TG128	190,107 PP512	arki05	17 Sep 2026	View Benchmark
basecompute/Qwen3-0.6B BaseRT 0.2.4Q4	Apple M5 Max Metal	708.3 TG128	34,136 PP512	basecompute	10 Sep 2026	View Benchmark
basecompute/Qwen3-0.6B BaseRT 0.2.5Q4	Apple M5 Max Metal	698.5 TG128	32,977 PP512	lukas	18 Sep 2026	View Benchmark
Qwen3-0.6B-Q4 BaseRT 0.2.6Q4	Apple M4 Max Metal	583.3 TG128 @ 1 ctx	9,998 PP512	basecompute	19 Sep 2026	View Benchmark
basecompute/Qwen3-0.6B BaseRT 0.2.4Q8	Apple M5 Max Metal	549.5 TG128	33,088 PP512	basecompute	10 Sep 2026	View Benchmark
basecompute/Qwen3-0.6B BaseRT 0.2.4Q4	Apple M5 Pro Metal	516.8 TG128	20,778 PP512	arki05	11 Sep 2026	View Benchmark
basecompute/Qwen3-0.6B BaseRT 0.2.4Q4	Apple M5 Pro Metal	512.0 TG128	20,603 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-0.6B-Q4 BaseRT 0.2.6Q4	Apple M3 Ultra Metal	501.7 TG128 @ 1 ctx	12,830 PP512	basecompute	19 Sep 2026	View Benchmark
basecompute/Qwen3-0.6B BaseRT 0.2.5Q4	Apple M5 Pro Metal	481.5 TG128 @ 1 ctx	19,595 PP512	isu	18 Sep 2026	View Benchmark
Qwen3-0.6B-Q4 BaseRT 0.2.6Q4	NVIDIA GB10 CUDA	458.8 TG128 @ 1 ctx	20,970 PP512	basecompute	19 Sep 2026	View Benchmark
Qwen3-0.6B-cuda-q4 BaseRT 0.2.6Q4	NVIDIA GB10 CUDA	456.1 TG128 @ 1 ctx	52,750 PP512	basecompute	19 Sep 2026	View Benchmark
Qwen3-0.6B-Q8 BaseRT 0.2.6Q8	Apple M4 Max Metal	455.8 TG128 @ 1 ctx	9,749 PP512	basecompute	19 Sep 2026	View Benchmark
Qwen3-0.6B-Q8 BaseRT 0.2.6Q8	Apple M3 Ultra Metal	440.2 TG128 @ 1 ctx	12,494 PP512	basecompute	19 Sep 2026	View Benchmark
basecompute/gemma-3-1b-it BaseRT 0.2.5Q4	Apple M5 Max Metal	415.5 TG128	19,770 PP512	lukas	17 Sep 2026	View Benchmark
basecompute/gemma-3-1b-it BaseRT 0.2.5Q4	Apple M5 Max Metal	414.2 TG128	23,019 PP512	lukas	18 Sep 2026	View Benchmark
Qwen3-0.6B-cuda-q4mix BaseRT 0.2.6Q4	NVIDIA GB10 CUDA	413.2 TG128 @ 1 ctx	49,865 PP512	basecompute	19 Sep 2026	View Benchmark
Llama-3.2-1B-Instruct-Q4 BaseRT 0.2.6Q4	Apple M3 Ultra Metal	410.1 TG128 @ 1 ctx	9,066 PP512	basecompute	20 Sep 2026	View Benchmark
Llama-3.2-1B-Instruct-Q4 BaseRT 0.2.6Q4	Apple M4 Max Metal	371.7 TG128 @ 1 ctx	5,963 PP512	basecompute	19 Sep 2026	View Benchmark
gemma-3-1b-it-Q4 BaseRT 0.2.6Q4	Apple M4 Max Metal	361.2 TG128 @ 1 ctx	7,448 PP512	basecompute	19 Sep 2026	View Benchmark
basecompute/Qwen3-0.6B BaseRT 0.2.4Q8	Apple M5 Pro Metal	350.2 TG128	20,537 PP512	arki05	11 Sep 2026	View Benchmark
basecompute/Qwen3-0.6B BaseRT 0.2.4Q8	Apple M5 Pro Metal	349.8 TG128	20,366 PP512	arki05	11 Sep 2026	View Benchmark
Llama-3.2-1B-Instruct-Q8 BaseRT 0.2.6Q4	Apple M3 Ultra Metal	345.2 TG128 @ 1 ctx	9,055 PP512	basecompute	20 Sep 2026	View Benchmark
gemma-3-1b-it-Q4 BaseRT 0.2.6Q4	Apple M3 Ultra Metal	328.0 TG128 @ 1 ctx	9,903 PP512	basecompute	20 Sep 2026	View Benchmark
Llama-3.2-1B-Instruct-Q8 BaseRT 0.2.6Q4	Apple M4 Max Metal	320.5 TG128 @ 1 ctx	6,058 PP512	basecompute	19 Sep 2026	View Benchmark
Qwen3-1.7B-Q4 BaseRT 0.2.6Q4	Apple M4 Max Metal	318.4 TG128 @ 1 ctx	4,146 PP512	basecompute	19 Sep 2026	View Benchmark

Side B · llama.cpp

Top 25 of 149 runs by decode throughput.

Model / format	Chip / backend	Decode	Prefill	Contributor	Date	Report
Tinystories Lay8 Hs512 Hd8 33M llama.cpp b10809 (5266f24da)Q4_0	Apple M5 Pro BLAS + Metal	1,443.3 TG128	124,181 PP512	arki05	17 Sep 2026	View Benchmark
Qwen3-0.6B llama.cpp b10809 (5266f24da)Q4_K_M	AMD Radeon RX 7900 XT (RADV NAVI31) Vulkan	508.8 TG128	26,137 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-0.6B llama.cpp b10809 (5266f24da)Q4_K_M	AMD Radeon RX 7900 XT (RADV NAVI31) Vulkan	491.9 TG128	25,964 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-0.6B llama.cpp b10809 (5266f24da)Q8_0	AMD Radeon RX 7900 XT (RADV NAVI31) Vulkan	479.4 TG128	26,346 PP512	arki05	11 Sep 2026	View Benchmark
Models Qwen Qwen3 0.6B llama.cpp b10360 (48d22e295)Q4_K_M	Apple M5 Max BLAS + Metal	439.1 TG128	24,365 PP512	basecompute	10 Sep 2026	View Benchmark
Qwen3 0.6B Instruct llama.cpp b10360 (48d22e295)Q8_0	Apple M5 Max BLAS + Metal	379.0 TG128	24,983 PP512	basecompute	10 Sep 2026	View Benchmark
Qwen3-0.6B llama.cpp b10809 (5266f24da)Q4_K_M	AMD Radeon RX 7900 XT ROCm	368.6 TG128	23,972 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-0.6B llama.cpp b10809 (5266f24da)Q4_K_M	AMD Radeon RX 7900 XT ROCm	367.7 TG128	23,718 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-0.6B llama.cpp b10809 (5266f24da)Q4_K_M	Apple M5 Pro BLAS + Metal	358.3 TG128	14,509 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-0.6B llama.cpp b10809 (5266f24da)Q4_K_M	Apple M5 Pro BLAS + Metal	358.1 TG128	14,344 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-0.6B llama.cpp b10809 (5266f24da)Q4_K_M	Apple M5 Pro BLAS + Metal	356.2 TG128	14,552 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-0.6B llama.cpp b10809 (5266f24da)Q8_0	AMD Radeon RX 7900 XT ROCm	313.7 TG128	24,691 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-0.6B llama.cpp b10809 (5266f24da)Q8_0	Apple M5 Pro BLAS + Metal	283.0 TG128	14,942 PP512	arki05	11 Sep 2026	View Benchmark
Llama-3.2-3B-Instruct llama.cpp b10809 (5266f24da)Q4_K_M	AMD Radeon RX 7900 XT (RADV NAVI31) Vulkan	229.7 TG128	5,737 PP512	arki05	11 Sep 2026	View Benchmark
Llama-3.2-3B-Instruct llama.cpp b10809 (5266f24da)Q4_K_M	AMD Radeon RX 7900 XT (RADV NAVI31) Vulkan	223.4 TG128	5,721 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-30B-A3B-Instruct-2507 llama.cpp b10809 (5266f24da)Q2_K	AMD Radeon RX 7900 XT (RADV NAVI31) Vulkan	198.1 TG128	2,837 PP512	arki05	11 Sep 2026	View Benchmark
Gpt-Oss-20B llama.cpp b10809 (5266f24da)Q4_K_M	AMD Radeon RX 7900 XT (RADV NAVI31) Vulkan	195.6 TG128	3,292 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-30B-A3B-Instruct-2507 llama.cpp b10809 (5266f24da)Q4_K_M	AMD Radeon RX 7900 XT (RADV NAVI31) Vulkan	186.7 TG128	2,868 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-4B-Instruct-2507 llama.cpp b10809 (5266f24da)Q4_K_M	AMD Radeon RX 7900 XT (RADV NAVI31) Vulkan	185.1 TG128	4,783 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-30B-A3B-Instruct-2507 llama.cpp b10809 (5266f24da)Q3_K_M	AMD Radeon RX 7900 XT (RADV NAVI31) Vulkan	184.5 TG128	2,474 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-30B-A3B-Instruct-2507 llama.cpp b10809 (5266f24da)Q4_K_M	AMD Radeon RX 7900 XT (RADV NAVI31) Vulkan	181.3 TG128	2,827 PP512	arki05	11 Sep 2026	View Benchmark
Qwen3-4B-Instruct-2507 llama.cpp b10809 (5266f24da)Q4_K_M	AMD Radeon RX 7900 XT (RADV NAVI31) Vulkan	180.3 TG128	4,793 PP512	arki05	11 Sep 2026	View Benchmark
Qwen2.5 Coder 1.5B Instruct GGUF llama.cpp b10902 (df03399b8)Q4_K_M	NVIDIA GeForce RTX 4060 Laptop GPU CUDA	178.8 TG128	9,465 PP512	sarthak247	11 Sep 2026	View Benchmark
Llama-3.2-3B-Instruct llama.cpp b10809 (5266f24da)Q4_K_M	AMD Radeon RX 7900 XT ROCm	172.0 TG128	6,980 PP512	arki05	11 Sep 2026	View Benchmark
Llama-3.2-3B-Instruct llama.cpp b10809 (5266f24da)Q4_K_M	AMD Radeon RX 7900 XT ROCm	171.9 TG128	6,832 PP512	arki05	11 Sep 2026	View Benchmark