AI Battle > Rankings > Coding Agent Index

Coding Agent Index Ranking — Coding Agents (2026)

null by null leads the Coding Agent Index ranking with a score of 0.62. The ranking covers 10 evaluated coding agents from a public dataset that AI Battle re-checks daily.

Last updated: . Source: public benchmark datasets and provider pricing, aggregated daily; 10 entries shown.

Claude Code - Fable 5.1 (max) (with fallback0.62Codex - GPT-6 Astra (max)0.62Claude Code - Opus 5 (max)0.60Muse Code - Muse Spark 1.3 (max)0.54Opencode - GLM-5.30.54Kimi Code CLI - Kimi K30.52Grok Build - Grok 4.6 (xhigh)0.47Claude Code - Qwen3.8 Max0.43Codex - DeepSeek V4 Pro 0813 (max)0.43Antigravity SDK - Gemini 3.8 Flash (high)0.42
Every entry in the dataset, scaled from the smallest to the largest published value.

All 10 entries in this dataset

#EntryCreatorValueΔ vs #1
1Claude Code - Fable 5.1 (max) (with fallback)0.620.0%
2Codex - GPT-6 Astra (max)0.62-0.9%
3Claude Code - Opus 5 (max)0.60-4.0%
4Muse Code - Muse Spark 1.3 (max)0.54-12.7%
5Opencode - GLM-5.30.54-13.9%
6Kimi Code CLI - Kimi K30.52-16.5%
7Grok Build - Grok 4.6 (xhigh)0.47-24.5%
8Claude Code - Qwen3.8 Max0.43-30.5%
9Codex - DeepSeek V4 Pro 0813 (max)0.43-30.8%
10Antigravity SDK - Gemini 3.8 Flash (high)0.42-32.7%

How the values are distributed

Across the 10 numeric entries in this window the median is 0.53 and the mean is 0.52, so the typical entry sits 0.09 below the leader. The window spans 0.42 to 0.62.

30112003
8 equal buckets between the smallest (0.42) and largest (0.62) value; numbers under bars are entry counts.

5 of 10 entries are at or above the median, and the top three hold 35% of the combined value — read it against the metric below, since a higher number is not "better" for every dataset.

Who publishes these entries

The source dataset for this family does not publish a provider or creator label per entry, so AI Battle cannot group them: the table above is the complete published list. Where the dataset does carry a label (model, gateway and tool families do), this section names the creators and how many entries each holds.

Metric reference

This ranking carries the metric codingAgentsIndex from the Coding Agent Index dataset in the tab::agents-coding family. Units and the direction of "better" are not declared by the source dataset, so AI Battle does not invent them: values are shown exactly as published, and the ordering is the source dataset's own.

How this ranking is built

Rebuilt on from the public dataset Coding Agent Index (family tab::agents-coding). The source lists 10 entries and all 10 are shown here. AI Battle requests the dataset's rows, keeps the ordering the source publishes, and computes only the statistics on this page: median, mean, spread, the #1–#2 gap, the creator breakdown and the raw-data file. Nothing on this page is generated text about the entries — the numbers come from the source.

Refresh cadence: every deploy re-pulls the dataset, so this page tracks the source's own update cycle. Corrections: see the methodology page.

Limitations

Raw data

Machine-readable copy of this table, with the statistics below and the source provenance: /data/rankings/agents-coding-coding-agent-index.json. Free to reuse with attribution to AI Battle and the source dataset.

FAQ — Coding Agent Index

What is the best model for Coding Agent Index in 2026?

null by null currently leads the Coding Agent Index ranking with a score of 0.62, the highest value in this dataset across Coding Agents. AI Battle aggregates the dataset from its public source and re-checks it daily.

How often is the Coding Agent Index ranking updated?

The Coding Agent Index ranking is rebuilt daily from the upstream public dataset. Scores are the source dataset's own published values, so positions track whatever that source last released — each ranking page names the dataset it comes from.

Which models rank in the top 3 for Coding Agent Index?

The top 3 are: 1. null (0.62), 2. null (0.62), 3. null (0.60).

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