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)

Sep 16, 6:09 PM

e125b99

PolkaJam (Recompiler)

Rust

1.5x faster1.87ms

PolkaJamBaseline

Rust

baseline2.74ms

SpaceJam

Rust

1.4x slower3.79ms

TurboJam

C++

1.6x slower4.29ms

JAM DUNA

1.9x slower5.29ms

JamZig

Zig

2.9x slower8.05ms

JavaJAM

Java

3.7x slower10.02ms

Jamzilla

5.4x slower14.92ms

Vinwolf

Rust

5.0x slower13.66ms

FastRoll

Rust

6.2x slower16.98ms

Boka

Swift

12.6x slower34.50ms

TSJam

TypeScript

15.8x slower43.33ms

Jamixir

Elixir

14.8x slower40.68ms

JamPy

Python

18.3x slower50.06ms

PyJAMaz

Python

26.0x slower71.35ms

Linear scale • Lower is better

Percentiles:

P50

P90

P99

<1.2x

<2x

<10x

>50x

Performance Rankings

Baseline: PolkaJam(Score: 3.2)

Rank	Team	Language	Score	P50 (ms)	P90 (ms)	Relative Performance
1	PolkaJam (Recompiler)	Rust	2.0	2.06	2.28	1.5x faster
2	PolkaJam	Rust	3.2	2.92	4.16	baseline
3	SpaceJam	Rust	4.5	3.13	5.90	1.4x slower
4	TurboJam	C++	5.4	3.50	7.83	1.6x slower
5	JAM DUNA	Go	6.2	5.23	7.33	1.9x slower
6	JamZig	Zig	10.6	5.81	10.89	2.9x slower
7	JavaJAM	Java	12.9	9.89	16.30	3.7x slower
8	Jamzilla	Go	19.5	9.60	20.34	5.4x slower
9	Vinwolf	Rust	19.7	5.84	10.84	5.0x slower
10	FastRoll	Rust	22.2	12.42	23.49	6.2x slower
11	Boka	Swift	42.6	28.37	58.12	12.6x slower
12	TSJam	TypeScript	61.1	28.82	74.73	15.8x slower
13	Jamixir	Elixir	66.1	26.67	76.10	14.8x slower
14	JamPy	Python	72.6	33.91	99.45	18.3x slower
15	PyJAMaz	Python	103.8	55.65	130.62	26.0x slower

Audit Time Calculator

Baseline Audit Time (days)

Time required for polkajam to complete audit

1PolkaJam (Recompiler)

2.0d

2PolkaJam

3.0d

3SpaceJam

4.1d

4TurboJam

4.7d

5JAM DUNA

5.8d

6JamZig

8.8d

7JavaJAM

11.0d

8Jamzilla

16.3d

9Vinwolf

15.0d

10FastRoll

18.6d

11Boka

37.8d

12TSJam

47.4d

13Jamixir

44.5d

14JamPy

54.8d

15PyJAMaz

78.1d

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: 0.7.0| Last updated: Sep 16, 2025, 6:09 PM| Source data from: Sep 16, 2025

Testing protocol conformance at scale. Learn more at jam-conformance | Commit e125b99 | View all clients