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Long-context understanding on LongBench (Task-Specific Metrics)

62.1Overall Average ScoreDPO w/ LongReward
28.40437.15245.954.648Mar 26, 2024Aug 9, 2024Dec 24, 2024May 9, 2025Sep 23, 2025Feb 6, 2026Jun 23, 2026

Evaluation results

MethodLinks
DPO w/ LongRewardBackbone=GLM-4-9B, Judge Model=GPT-4o, Prompting Protocol=zero-shot2024.1062.171.958.848.5—————
DPO w/ ContrastBackbone=GLM-4-9B, Judge Model=GPT-4o, Prompting Protocol=zero-shot2024.1060.567.85847.8—————
officially post-trainedBackbone=GLM-4-9B, Judge Model=GPT-4o, Prompting Protocol=zero-shot2024.1060.367.856.947.9—————
DPO w/ LongRewardBackbone=Llama-3.1-8B, Judge Model=GPT-4o, Prompting Protocol=zero-shot2024.1059.967.855.843.2—————
DPO w/ SRMBackbone=GLM-4-9B, Judge Model=GPT-4o, Prompting Protocol=zero-shot2024.1059.967.557.448.2—————
SFTBackbone=GLM-4-9B, Judge Model=GPT-4o, Prompting Protocol=zero-shot2024.1056.668.450.942.1—————
DPO w/ SRMBackbone=Llama-3.1-8B, Judge Model=GPT-4o, Prompting Protocol=zero-shot2024.1056.26549.642.7—————
DPO w/ ContrastBackbone=Llama-3.1-8B, Judge Model=GPT-4o, Prompting Protocol=zero-shot2024.1056.267.846.240.3—————
Vanilla / Lossless SDTarget Model=Qwen2.5-72B-Instruct, KV Budget=—2026.0655.8144.235727.5472.556066.7——
DustinTarget Model=Qwen2.5-72B-Instruct, KV Budget=5122026.0655.2344.2356.3527.171.236065.97——
SFTBackbone=Llama-3.1-8B, Judge Model=GPT-4o, Prompting Protocol=zero-shot2024.105566.144.539.6—————
DustinTarget Model=Llama-3.3-70B-Instruct, KV Budget=1282026.0653.8145.5559.0226.7568.1853.9662.78——
DustinTarget Model=Llama-3.3-70B-Instruct, KV Budget=5122026.0653.2345.2759.127.7670.1453.459.15——
DustinTarget Model=Qwen2.5-72B-Instruct, KV Budget=1282026.0652.4144.5955.3126.1468.3552.1361.3——
SnapKVTarget Model=Llama-3.3-70B-Instruct, KV Budget=5122026.0652.4144.4559.5824.8768.7553.3958.82——
SnapKVTarget Model=Qwen2.5-72B-Instruct, KV Budget=5122026.0651.942.858.7723.0271.215557.29——
Vanilla / Lossless SDTarget Model=Llama-3.3-70B-Instruct, KV Budget=—2026.0650.9445.4858.8828.5870.7553.6349.64——
ClassicSD / MagicDecTarget Model=Llama-3.1-8B-Instruct, KV Budget=—2026.0650.5842.3444.1529.1169.3852.7559.72——
DustinTarget Model=Llama-3.1-8B-Instruct, KV Budget=5122026.0650.4542.2644.2628.6369.0852.7559.68——
SnapKVTarget Model=Llama-3.3-70B-Instruct, KV Budget=1282026.0650.3239.1758.0222.0764.5554.6358.53——
DeltaKV†Backbone=Llama-3.1-8B, KR=45, CR=30, variant=lightweight decompressor2026.0250.343.246.827.769.554.859.74530
DeltaKVBackbone=Llama-3.1-8B, KR=29, CR=30, quantization=4-bit2026.0250.343.346.627.369.854.460.52930
OmniKVBackbone=Llama-3.1-8B, KR=100, CR=302026.0250.244.846.128.968.952.859.910030
DeltaKVBackbone=Llama-3.1-8B, KR=45, CR=302026.0250.244.445.927.669.753.460.24530
OmniKVBackbone=Llama-3.1-8B, KR=100, CR=202026.0250.14345.727.568.654.960.810020
GPT-4Length=128k2024.0850————————
Llama-3.1-8BBackbone=Llama-3.1-8B, KR=100, CR=1002026.025045.346.228.769.452.757.9100100
QuestBackbone=Llama-3.1-8B, KR=100, CR=302026.025044.446.229.36953.157.610030
DustinTarget Model=Llama-3.1-8B-Instruct, KV Budget=2562026.0649.8142.1544.3127.7268.7752.5958.11——
SnapKVBackbone=Llama-3.1-8B, KR=30, CR=302026.0249.844.546.426.568.252.760.33030
DeltaKV†Backbone=Llama-3.1-8B, KR=43, CR=20, variant=lightweight decompressor2026.0249.842.746.226.268.754.360.54320
AdaKVBackbone=Llama-3.1-8B, KR=30, CR=302026.0249.744.746.526.669.352.758.33030
QuestBackbone=Llama-3.1-8B, KR=100, CR=202026.0249.742.246.928.868.954.956.510020
PyramidKVBackbone=Llama-3.1-8B, KR=30, CR=302026.0249.544.146.32668.552.659.13030
officially post-trainedBackbone=Llama-3.1-8B, Judge Model=GPT-4o, Prompting Protocol=zero-shot2024.1049.459.342.935.3—————
SnapKVBackbone=Llama-3.1-8B, KR=20, CR=202026.0249.242.945.425.868.854.857.42020
DustinTarget Model=Llama-3.1-8B-Instruct, KV Budget=1282026.0649.0241.9543.9925.0368.4252.8457.15——
Quest*Target Model=Llama-3.3-70B-Instruct, KV Budget=5122026.0648.9640.3452.2427.1866.6354.6151.95——
Gemini-1.5-ProLength=128k2024.0848.5————————
ChatGLM3-6BModel Scale=< 7B2024.0348.440.9452656.56557.1——
Qwen2.5-32BBackbone=Qwen2.5-32B, KR=100, CR=1002026.0248.442.754.327.367.65642.6100100
InternLM2-Chat-7B-SFTModel Scale=< 7B2024.0348.147.345.225.359.967.243.5——
OmniKVBackbone=Qwen2.5-32B, KR=100, CR=202026.0248.142.454.226.967.256.141.710020
DeltaKVBackbone=Qwen2.5-32B, KR=44, CR=202026.0247.741.954.226.266.155.442.14420
Quest*Target Model=Qwen2.5-72B-Instruct, KV Budget=5122026.0647.6936.9141.825.9264.455.0857.24——
Qwen2.5-7BBackbone=Qwen2.5-7B, KR=100, CR=1002026.0247.642.549.628.668.753.842.5100100
OmniKVBackbone=Qwen2.5-7B, KR=100, CR=302026.0247.441.949.428.469.15441.510030
DeltaKVBackbone=Qwen2.5-7B, KR=48, CR=302026.0247.141.84927.769.153.341.74830
SnapKVBackbone=Qwen2.5-32B, KR=20, CR=202026.0247.139.553.824.667.25641.72020
SnapKVTarget Model=Qwen2.5-72B-Instruct, KV Budget=1282026.0647.0836.5756.8919.863.7151.6351.54——
SnapKVBackbone=Qwen2.5-7B, KR=30, CR=302026.024741.748.826.668.354.541.83030
InternLM2-Chat-20B-SFTModel Scale=13~20B2024.0346.846.848.725.651.267.940.4——
InternLM2-Chat-7BModel Scale=< 7B2024.0346.145.743.126.558.366.336.4——
PyramidKVBackbone=Qwen2.5-7B, KR=30, CR=302026.0246.140.648.724.467.754.540.63030
InternLM2-Chat-20BModel Scale=13~20B2024.0344.846.946.72649.167.332.6——
QuestTarget Model=Llama-3.1-8B-Instruct, KV Budget=5122026.0643.933.634.727.2155.9451.3354.92——
Original Promptcompression rate=none, LLM=LLaMA 3.1-8B2025.0743.0337.3536.3627.3971.01————
Llama3.1-70B-InstructLength=128k2024.0842.8————————
FullBackbone=Llama-3.1-8B2026.0241.4747.5143.2825.945.9268.1818.01——
MInferenceBackbone=Llama-3.1-8B2026.0241.1447.4242.5425.8545.5867.617.84——
PrismBackbone=Llama-3.1-8B2026.0241.0847.0942.132646.466.1518.72——
XAttentionBackbone=Llama-3.1-8B2026.0239.6845.8941.5626.1845.8659.3219.24——
StreamingLLMTarget Model=Llama-3.3-70B-Instruct, KV Budget=5122026.0639.6132.3639.3523.0151.5551.0541.98——
FullBackbone=Qwen-3-8B2026.0239.4947.140.4524.0756.69671.65——
MInferenceBackbone=Qwen-3-8B2026.0239.1846.940.3924.0755.7466.331.61——
PrismBackbone=Qwen-3-8B2026.0239.1246.4740.0824.0158.3664.171.64——
XAttentionBackbone=Qwen-3-8B2026.0238.8244.4940.0924.1257.2765.671.29——
PaluBackbone=Qwen2.5-7B, KR=50, CR=1002026.0238.834.435.627.568.74521.350100
Mistral-7B-Instruct-v0.2Model Scale=< 7B2024.0338.331.326.421.846.659.244.8——
QuestTarget Model=Llama-3.1-8B-Instruct, KV Budget=2562026.0638.1527.6124.6424.4548.6748.3749.86——
Quest*Target Model=Qwen2.5-72B-Instruct, KV Budget=1282026.0637.0123.1225.2121.6752.8149.746.37——
Mixtral-8x7B-Instruct-v0.1Model Scale=13~20B2024.03373525.617.135.968.240——
StreamingLLMTarget Model=Llama-3.3-70B-Instruct, KV Budget=1282026.0636.9427.1339.7819.0246.4352.4439.49——
FlexPrefillBackbone=Qwen-3-8B2026.0236.1343.7739.3123.9957.3350.51.87——
StreamingLLMTarget Model=Llama-3.1-8B-Instruct, KV Budget=5122026.063628.3530.1123.1650.5147.1138.31——
CREAM-7B-32kContext Window Length=32k, Instruction-tuning steps=100, Training data length=4K, base_model=LLaMa2-7B-Chat2024.0635.934.831.127.265.1750.4——
DACcompression rate=0.5, SLM=LLaMA 3.2-1B, LLM=LLaMA 3.1-8B2025.0735.4232.6828.0822.9258.01————
StreamingLLMTarget Model=Qwen2.5-72B-Instruct, KV Budget=5122026.0635.2527.6133.8221.754.5739.8435.02——
LLMLingua-2compression rate=0.5, SLM=LLaMA 3.2-1B, LLM=LLaMA 3.1-8B2025.0734.8232.5127.9322.7456.08————
StreamingLLMTarget Model=Llama-3.1-8B-Instruct, KV Budget=2562026.0634.3925.8429.7321.1647.647.0636.83——
LongChat-v1.5-7B-32kContext Window Length=32k2024.0634.328.720.626.76015.854.1——
FlexPrefillBackbone=Llama-3.1-8B2026.0233.946.1341.4925.8546.6325.6117.68——
LLMLinguacompression rate=0.5, SLM=LLaMA 3.2-1B, LLM=LLaMA 3.1-8B2025.0733.3127.8124.6823.1357.63————
Quest*Target Model=Llama-3.3-70B-Instruct, KV Budget=1282026.0633.2123.6627.9321.0947.9444.235.67——
StreamingLLMTarget Model=Llama-3.1-8B-Instruct, KV Budget=1282026.0632.8625.0229.4619.2543.9445.2335.79——
StreamingLLMTarget Model=Qwen2.5-72B-Instruct, KV Budget=1282026.0632.7223.2732.4917.5848.4842.6933.68——
Selective-Contextcompression rate=0.5, SLM=LLaMA 3.2-1B, LLM=LLaMA 3.1-8B2025.0732.1626.424.7821.9855.47————
Qwen2-7B-InstructLength=128k2024.0831.9————————
Vicuna-v1.5-7B-16kContext Window Length=16k2024.0631.92818.62666.25.547.3——
Gradient-Llama3-70BLength=128k2024.0831.8————————
WINABackbone=Phi-4-16k, Sparsity=0.52025.0531.3921.1915.9813.3959.3948.7636.53——
Qwen2-72B-InstructLength=128k2024.0831————————
Llama2-7B-chat-4kContext Window Length=4k2024.063124.922.624.7605.948.1——
Baichuan2-13B-ChatModel Scale=13~20B2024.0330.934.329.121.345.5451.4——
TEALBackbone=Phi-4-16k, Sparsity=0.52025.0530.5422.1511.6915.0458.4451.0329.51——
Yi-9B-200kLength=128k2024.0830.3————————
WINABackbone=Phi-4-16k, Sparsity=0.652025.0530.2616.312.2417.3659.2246.5837.6——
TEALBackbone=Phi-4-16k, Sparsity=0.652025.0530.0719.2514.1119.559.4843.5225.71——
Llama3.1-8B-InstructLength=128k2024.0830————————
Qwen-14B-ChatModel Scale=13~20B2024.0329.732.619.422.536.923.742.9——