Update benchmark results
Browse files
README.md
CHANGED
|
@@ -80,22 +80,21 @@ instructions and serving examples once the integration is publicly available.
|
|
| 80 |
|
| 81 |
## Benchmark results
|
| 82 |
|
| 83 |
-
|
| 84 |
-
|
| 85 |
-
|
| 86 |
-
|
| 87 |
-
|
| 88 |
-
|
|
| 89 |
-
|
|
| 90 |
-
|
|
| 91 |
-
|
|
| 92 |
-
|
|
| 93 |
-
|
| 94 |
-
|
| 95 |
-
|
| 96 |
-
|
| 97 |
-
|
| 98 |
-
reported alongside the results.
|
| 99 |
|
| 100 |
## Citation
|
| 101 |
|
|
|
|
| 80 |
|
| 81 |
## Benchmark results
|
| 82 |
|
| 83 |
+
All methods use **block size 16**, TP1, concurrency 1, BF16, and greedy
|
| 84 |
+
no-thinking decoding. UBTree uses a 49-node tree.
|
| 85 |
+
|
| 86 |
+
Each cell shows **acceptance length / E2E speedup over target-only AR**.
|
| 87 |
+
|
| 88 |
+
| Dataset | UBTree | DFlash | DSpark |
|
| 89 |
+
|---|---:|---:|---:|
|
| 90 |
+
| GSM8K | **9.53 / 3.055×** | 6.57 / 2.665× | 7.53 / 2.718× |
|
| 91 |
+
| MATH-500 | **9.86 / 3.518×** | 5.74 / 2.643× | 6.96 / 2.826× |
|
| 92 |
+
| AIME 2025 | **8.44 / 3.152×** | 4.76 / 2.261× | 5.37 / 2.263× |
|
| 93 |
+
| HumanEval | **10.04 / 3.411×** | 6.39 / 2.770× | 7.59 / 2.914× |
|
| 94 |
+
| MBPP | **9.35 / 3.062×** | 5.87 / 2.473× | 7.16 / 2.678× |
|
| 95 |
+
| LiveCodeBench | **7.46 / 2.794×** | 4.11 / 1.948× | 4.84 / 2.030× |
|
| 96 |
+
|
| 97 |
+
AL and throughput use three-round medians; the matched AR baseline uses one round.
|
|
|
|
| 98 |
|
| 99 |
## Citation
|
| 100 |
|