pondus 0.4.1

Opinionated AI model benchmark aggregator — install via cargo: cargo install pondus

pondus

Opinionated AI model benchmark aggregator.

What it does

Aggregates AI model benchmark data from 8 trusted sources into a unified JSON schema. Designed for AI agents (Claude Code, etc.) to consume programmatically. Caches results for 24h to avoid rate limiting.

Sources

Source	Type	Data
Artificial Analysis	agent-browser scrape	Intelligence index, speed, pricing
LM Arena (LMSYS)	Community JSON	ELO ratings from human preferences
SWE-bench	GitHub JSON	Code generation resolve rates
SWE-rebench	agent-browser scrape	Code generation resolve rates (rebench variant)
Aider	GitHub YAML	Polyglot coding benchmark pass rates
LiveBench	HuggingFace API	Multi-domain benchmark scores
Terminal-Bench	HuggingFace YAML	Terminal/CLI task completion
SEAL	agent-browser scrape	Scale AI multi-benchmark evaluations

Note: Sources marked "agent-browser scrape" require the agent-browser CLI. All other sources work out of the box. LiveBench data depends on the upstream HuggingFace dataset which may lag behind other sources.

Installation

cargo install pondus

Usage

pondus rank                     # rank all models (default command)
pondus                          # same as `pondus rank`
pondus rank --top 10            # top 10 only
pondus check claude-opus-4.6    # check one model across all sources
pondus compare gpt-5.2 claude-opus-4.6  # head-to-head comparison
pondus sources                  # show source status
pondus refresh                  # clear cache and re-fetch

Global Flags

Flag	Description
`--format json	table
--refresh	Bypass cache for this run

Configuration

Config location: ~/.config/pondus/config.toml

[cache]
ttl_hours = 24

[alias]
path = "models.toml"  # relative to config dir, or absolute path

[sources.artificial_analysis]
api_key = "your-key"  # optional, for AA source

[sources.agent_browser]
path = "agent-browser"  # path to agent-browser CLI

Model Aliases

Different benchmarks use different naming conventions. models.toml maps canonical model names to source-specific variants:

[claude-opus-4_6]
canonical = "claude-opus-4.6"
aliases = [
  "Claude Opus 4.6",
  "claude-opus-4-6",
  "anthropic/claude-opus-4.6",
  "Opus 4.6",
]

When you run pondus check opus-4.6, pondus resolves the alias to the canonical name and matches across all sources. Prefix matching also works automatically — gemini-2.5-pro-preview-06-05 matches gemini-2.5-pro since the suffix starts with -. PRs welcome to add new models.

Output Format

Default JSON output:

{
  "timestamp": "2026-02-27T10:30:00Z",
  "query": { "query_type": "rank" },
  "sources": [
    {
      "source": "arena",
      "status": "ok",
      "scores": [
        { "model": "gpt-5.2", "rank": 1, "metrics": { "elo": 1350 } }
      ]
    }
  ]
}

Contributing

• Add a model: Add an entry to models.toml with canonical name and known aliases
• Add a source: Implement the Source trait in src/sources/

PRs welcome.

License

MIT

Sister Tools

Part of a family of AI-augmented CLI tools:

• lustro — AI news aggregator
• consilium — Multi-model deliberation
• hexis — Meta-cognitive framework