JAM

Conformance Performance

Important Note

This leaderboard highlights performance differences between JAM implementations. All implementations are works in progress and none are fully conformant yet. The rankings serve to track relative performance improvements over time.

Performance Comparison

All implementations relative to polkajam(aggregate weighted scores - see methodology below)

May 4, 9:04 AM

1062052

Jamzilla

baseline0.92ms

jamzilla-int

1.4x slower1.25ms

JavaJAM

Java

1.8x slower1.65ms

TurboJam

C++

2.7x slower2.48ms

Vinwolf

Rust

4.4x slower4.01ms

Typeberry

TypeScript

8.7x slower8.00ms

JAM Forge

Scala

8.8x slower8.14ms

Boka

Swift

13.9x slower12.76ms

jotl

16.2x slower14.92ms

New JAMneration

19.9x slower18.30ms

PyJAMaz

Python

22.1x slower20.38ms

jampy-recompiler

23.8x slower21.88ms

JamPy

Python

27.8x slower25.60ms

Jam4s

Scala

29.5x slower27.15ms

GrayMatter

Elixir

27.5x slower25.36ms

PBnJAM

TypeScript

59.9x slower55.16ms

Logarithmic scale • Lower is better

Percentiles:

P50

P90

P99

<1.2x

<2x

<10x

>50x

Performance Rankings

Baseline: polkajam(Score: )

Rank	Team	Language	Score	P50 (ms)	P90 (ms)	Relative Performance
1	Jamzilla	Go	1.2	0.71	1.46	baseline
2	jamzilla-int		1.8	0.87	2.26	1.4x slower
3	JavaJAM	Java	1.9	1.76	2.30	1.8x slower
4	TurboJam	C++	3.0	2.48	3.68	2.7x slower
5	Vinwolf	Rust	4.8	3.97	6.42	4.4x slower
6	Typeberry	TypeScript	9.9	7.45	13.76	8.7x slower
7	JAM Forge	Scala	11.4	6.17	13.38	8.8x slower
8	Boka	Swift	17.2	10.27	21.21	13.9x slower
9	jotl		19.9	11.59	19.68	16.2x slower
10	New JAMneration	Go	25.2	11.88	26.04	19.9x slower
11	PyJAMaz	Python	26.6	23.13	29.45	22.1x slower
12	jampy-recompiler		30.6	17.33	40.72	23.8x slower
13	JamPy	Python	36.8	19.50	49.06	27.8x slower
14	Jam4s	Scala	37.8	25.68	49.41	29.5x slower
15	GrayMatter	Elixir	39.6	18.00	40.44	27.5x slower
16	PBnJAM	TypeScript	66.0	51.07	72.29	59.9x slower

Audit Time Calculator

Baseline Audit Time (days)

Time required for polkajam to complete audit

1Jamzilla

3.0d

2jamzilla-int

4.1d

3JavaJAM

5.4d

4TurboJam

8.1d

5Vinwolf

13.1d

6Typeberry

26.1d

7JAM Forge

26.5d

8Boka

41.6d

9jotl

48.6d

10New JAMneration

59.6d

11PyJAMaz

66.4d

12jampy-recompiler

71.3d

13JamPy

83.4d

14Jam4s

88.5d

15GrayMatter

82.6d

16PBnJAM

179.7d

Note: These calculations show the real-world impact of performance differences on audit requirements.

Scoring Methodology

Weighted scoring system that considers full performance distribution. Our scoring system prioritizes consistent, predictable performance by weighing multiple statistical metrics:

Median (P50)

35%

Typical performance

90th Percentile

25%

Consistency

Mean

20%

Average

99th Percentile

10%

Worst case

Consistency

10%

Lower variance

How it works:

1. Performance measurements are based on the public W3F test vector traces
2. For each benchmark, we calculate a weighted score using the metrics above
3. We use geometric mean across all benchmarks to aggregate metrics
4. Teams are ranked by their final weighted score (lower is better)
5. Polkajam (interpreted) serves as the baseline (1.0x) for relative comparisons

Note: Only teams with data for all four benchmarks (Safrole, Fallback, Storage, Storage Light) are included in the overview. Zero values are excluded from calculations as they likely represent measurement errors.

Performance data updated regularly. Version: 0.7.2| Last updated: May 4, 2026, 9:04 AM| Source data from: May 4, 2026

Testing protocol conformance at scale. Learn more at jam-conformance | Commit 1062052 | View all clients | Download raw data