AIEvals

Benchmarks

Code Migration

Whether a model can reimplement a working program in another language and preserve its behaviour — the work of porting a tool to a new ecosystem or modernising legacy code, including COBOL to Java.

Agentic codingVals AI71 models run by Vals AIUpdated 29 September 2026

How it is run

Two task types: CLI migration between modern languages, and COBOL-to-Java modernisation. A migration is scored by the share of hidden behaviour tests the rebuilt program passes, and a separate anti-cheat check zeroes wrappers, copied reference artifacts and wrong-language submissions.

What it cannot tell you

Automated migration is far from turnkey: even the leader passes only about two-thirds of the hidden behaviour tests, so the ports mostly work but are not drop-in replacements. Serving speed can decide a score before capability does — Kimi K3 reaches 60.0% on COBOL-to-Java but 1.5% on CLI migration because its endpoint's latency exhausts the harness clock before it submits anything gradeable.

Leader
Claude Sonnet 5.569.83% · Vals AI's own list
Top-ten spread
16.91%Leader minus tenth place, or last place in smaller fields.
Median
29.95%of the 71 rows published
No published result
9of 46 models on this site

Independent leaderboard · Vals AI

Top 71 of 71 runs by Vals AI, one harness.

#ModelScore
1Claude Sonnet 5.569.83%
2Gemini 4 Argon68.17%
3GPT-6 Astra67.74%
4Claude Opus 5.566.65%
5GPT-6.1 Sol65.12%
6Claude Opus 557.47%
7GPT-6 Sol57.20%
8Claude Fable 555.06%
9Claude Fable 5.154.61%
10GPT-5.6 Sol52.92%
11GPT-5.6 Terra47.80%
12Hunyuan Hy4 Preview47.43%
13Muse Spark 1.3 Max47.41%
14Claude Opus 4.847.25%
15DeepSeek V4.1 Flash45.62%
16GPT-5.545.16%
17Grok 4.744.82%
18Grok 4.644.57%
19GPT-5.6 Luna44.55%
20Claude Sonnet 544.39%
21GLM 5.344.22%
22Claude Opus 4.743.88%
23MiMo V2.6 Pro43.01%
24GPT-6 Luna42.55%
25DeepSeek V4 Pro41.54%
26MiMo-V2.6-Flash40.93%
27Claude Sonnet 4 639.89%
28Deepseek V4 Flash 073138.63%
29Glm 5.237.87%
30Grok 4.536.60%
31Gemini 3.8 Flash36.55%
32Gpt 5.4 2026 03 0534.98%
33Gemini 3.7 Flash34.80%
34Muse Spark 1 131.11%
35Gemini 3.6 Flash30.93%
36Muse Spark 1.229.95%
37Kimi K2.627.77%
38Muse Spark 1 327.58%
39Gemini 3.5 Flash26.75%
40Deepseek V4 Pro26.20%
41Glm 5.125.77%
42Kimi K2.7 Code25.39%
43Qwen3.8 Max23.96%
44Mimo V2.5 Pro21.56%
45GLM 5.3 Flash20.52%
46MiniMax M319.93%
47Gemini 3.1 Pro17.31%
48Kimi K316.10%
49Gpt 5.4 Nano 2026 03 1714.47%
50Mimo V2.514.23%
51Qwen3.8 27b14.16%
52Inkling Small13.68%
53Qwen3.7 Max13.07%
54Gpt 5.4 Mini 2026 03 1712.94%
55Qwen3.7 Plus12.86%
56Inkling11.79%
57Qwen3.6 Plus11.10%
58MiniMax M2.78.69%
59Claude Haiku 4 5 20251001 Thinking7.55%
60Kimi K2.5 Thinking6.96%
61Grok 4.36.79%
62Gemini 3 Flash Preview6.39%
63Gemini 3.5 Flash Lite6.15%
64Mistral Medium 3.55.13%
65Nemotron 3 Ultra 550b A55b4.91%
66Gemini 3.1 Flash Lite Preview4.61%
67Mercury 2.54.49%
68Nemotron Lightning 3p5 30b A3b2.95%
69Ling 3.0 Flash Af Rc31.82%
70Grok 4.20 0309 Reasoning0.31%
71Ling 3.0 Flash 26070.00%

No published result tracked

9 of the 46 models on this site have no published number on this benchmark, so their cells in the home table stay blank rather than reading as zero.

Read this with

Benchmarks in the same category, which usually disagree with this one on purpose.

Sources

Every page used for this benchmark, read on 17 October 2026.