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Long-context evaluation on RULER 16k

95.02Total ScoreFull-KV
6.474429.462252.4575.4378Feb 3, 2026Feb 23, 2026Mar 16, 2026Apr 6, 2026Apr 26, 2026May 17, 2026Jun 7, 2026

Evaluation results

MethodLinks
Full-KVModel=Qwen2.5-32B, Compression Ratio=0%2026.0295.0210010010010099.810099.9599.8510097.796.279.462.4
HySparseModel Size=7B2026.0294.110010010099.499.696.696.789.897.260.895.5——
Full-AttnModel Size=80B2026.0293.610099.892.699.699.29397.394.995.474.580.4——
Full-AttnModel Size=7B2026.029310010010098.610096.499.299.494.437.197.4——
Hybrid SWAModel Size=7B2026.0291.610010099.897.699.896.697.494.799.123.798.5——
HySparseModel Size=80B2026.0290.610099.89998.210099.692.291.390.340.286.4——
LU-KVModel=Qwen2.5-32B, Compression Ratio=80%, Eviction Metric=π2 (KeyDiff Metric)2026.0288.8810010010010086.646.899.9599.2510096.0296.271.659
QUOKABackbone=Qwen-3-4B, BSA (Budget Size of Attention)=1,0242026.0288.57—————————————
Full-KVModel=Mistral-7B-v0.3, Compression Ratio=0%2026.0286.6394.296.499.697.495.676.888.6589.596.2882.2287.9371.650
BaselineComp (%)=0, Base Model=LongChat-v1.5-32K2026.0685.69—————————————
STAR-KVComp (%)=60, Base Model=LongChat-v1.5-32K2026.0684.16—————————————
AdaModel=Qwen2.5-32B, Compression Ratio=80%, Eviction Metric=π2 (KeyDiff Metric)2026.0280.8110010010099.844.22399.99999.8895.3499.074446.4
LU-KVModel=Qwen2.5-32B, Compression Ratio=80%, Eviction Metric=π1 (SnapKV Metric)2026.0280.4799.899.23284.271.878.485.884.699.7295.6693.136556.8
LU-KVModel=Mistral-7B-v0.3, Compression Ratio=80%, Eviction Metric=π2 (KeyDiff Metric)2026.0279.6685.676.61008790.835.292.8596.4592.1680.7886.864.646.8
UniformModel=Qwen2.5-32B, Compression Ratio=80%, Eviction Metric=π2 (KeyDiff Metric)2026.0274.981001001001008199.9599.498.9290.3699.3336.441.4
QUOKABackbone=GPT-OSS-20B, BSA (Budget Size of Attention)=1,0242026.0273.4—————————————
Hybrid SWAModel Size=80B2026.0272.795.294.870.893.286.469.483.257.866.713.369.2——
QUOKABackbone=Smollm3, BSA (Budget Size of Attention)=1,0242026.0272.69—————————————
QUOKABackbone=Llama-3.2-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.0270.9—————————————
PyramidModel=Qwen2.5-32B, Compression Ratio=80%, Eviction Metric=π2 (KeyDiff Metric)2026.0270.6810010099.899.610.299.9599.5584.5269.2698.9330.235.8
LU-KVModel=Mistral-7B-v0.3, Compression Ratio=80%, Eviction Metric=π1 (SnapKV Metric)2026.0269.9870.878.818.283.679.267.476.2567.895.8878.3284.476247
AdaModel=Mistral-7B-v0.3, Compression Ratio=80%, Eviction Metric=π2 (KeyDiff Metric)2026.0267.5192.691.297.487.86.81.286.458891.2875.4486.4736.436.6
QUOKABackbone=Qwen-2.5-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.0266.82—————————————
UniformModel=Mistral-7B-v0.3, Compression Ratio=80%, Eviction Metric=π2 (KeyDiff Metric)2026.0265.794.672.810078.87.40.886.194.894.1665.5690.8732.435.8
PyramidModel=Mistral-7B-v0.3, Compression Ratio=80%, Eviction Metric=π2 (KeyDiff Metric)2026.0265.5793.296.299.688.26.60.689.759294.3636.9288.7331.434.8
PaluComp (%)=60, Base Model=LongChat-v1.5-32K2026.0662.94—————————————
SampleAttnBackbone=Qwen-3-4B, BSA (Budget Size of Attention)=1,0242026.0259.57—————————————
SampleAttnBackbone=Smollm3, BSA (Budget Size of Attention)=1,0242026.0259.1—————————————
SampleAttnBackbone=Qwen-2.5-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.0256.64—————————————
SparQBackbone=Qwen-3-4B, BSA (Budget Size of Attention)=1,0242026.0256.02—————————————
SparQBackbone=Qwen-2.5-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.0254.71—————————————
LokiBackbone=GPT-OSS-20B, BSA (Budget Size of Attention)=1,0242026.0254.67—————————————
SampleAttnBackbone=GPT-OSS-20B, BSA (Budget Size of Attention)=1,0242026.0253.91—————————————
LokiBackbone=Qwen-3-4B, BSA (Budget Size of Attention)=1,0242026.0252.29—————————————
LokiBackbone=Smollm3, BSA (Budget Size of Attention)=1,0242026.0250.1—————————————
LokiBackbone=Qwen-2.5-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.0248.96—————————————
SparQBackbone=Llama-3.2-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.0248.59—————————————
SampleAttnBackbone=Llama-3.2-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.0248.31—————————————
AdaModel=Qwen2.5-32B, Compression Ratio=80%, Eviction Metric=π1 (SnapKV Metric)2026.0244.0498.852.64.421.874.218.2514.7599.3288.4894.5329.439
UniformModel=Qwen2.5-32B, Compression Ratio=80%, Eviction Metric=π1 (SnapKV Metric)2026.0243.9197.455.63.825.84.8219.614.499.2887.14942839
KeyDiffBackbone=Smollm3, BSA (Budget Size of Attention)=1,0242026.0241.64—————————————
LessIsMoreBackbone=GPT-OSS-20B, BSA (Budget Size of Attention)=1,0242026.0238.27—————————————
AdaModel=Mistral-7B-v0.3, Compression Ratio=80%, Eviction Metric=π1 (SnapKV Metric)2026.0237.485838.82.420.212.45.616.812.8592.0871.3686.1333.637
PyramidModel=Qwen2.5-32B, Compression Ratio=80%, Eviction Metric=π1 (SnapKV Metric)2026.0236.8383.8362.419.22014.9513.1593.6856.8495.7326.434.6
LessIsMoreBackbone=Smollm3, BSA (Budget Size of Attention)=1,0242026.0235.12—————————————
PyramidModel=Mistral-7B-v0.3, Compression Ratio=80%, Eviction Metric=π1 (SnapKV Metric)2026.0232.4350572.4284.80.221.5516.1562.3231.9482.23233
SparQBackbone=Smollm3, BSA (Budget Size of Attention)=1,0242026.0232.18—————————————
SparQBackbone=GPT-OSS-20B, BSA (Budget Size of Attention)=1,0242026.0230.75—————————————
LessIsMoreBackbone=Llama-3.2-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.0230.44—————————————
UniformModel=Mistral-7B-v0.3, Compression Ratio=80%, Eviction Metric=π1 (SnapKV Metric)2026.0229.5340.416.22.414.26.21119.6566.9266.9685.5329.833.6
LokiBackbone=Llama-3.2-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.0225.76—————————————
SnapKVBackbone=GPT-OSS-20B, BSA (Budget Size of Attention)=1,0242026.0224.82—————————————
LessIsMoreBackbone=Qwen-3-4B, BSA (Budget Size of Attention)=1,0242026.0224.39—————————————
KeyDiffBackbone=Llama-3.2-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.0224.29—————————————
SnapKVBackbone=Smollm3, BSA (Budget Size of Attention)=1,0242026.0224.21—————————————
KeyDiffBackbone=Qwen-3-4B, BSA (Budget Size of Attention)=1,0242026.0220.94—————————————
KeyDiffBackbone=GPT-OSS-20B, BSA (Budget Size of Attention)=1,0242026.0215.86—————————————
KeyDiffBackbone=Qwen-2.5-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.0215.79—————————————
LessIsMoreBackbone=Qwen-2.5-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.0212.84—————————————
SnapKVBackbone=Llama-3.2-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.0212.44—————————————
SnapKVBackbone=Qwen-3-4B, BSA (Budget Size of Attention)=1,0242026.0210.94—————————————
SnapKVBackbone=Qwen-2.5-3B-Instruct, BSA (Budget Size of Attention)=1,0242026.029.88—————————————