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Fastalytics

AI coding model leaderboard

Compare leading AI coding models using Artificial Analysis benchmark data, with developer-relevant context for coding scores, speed, latency, pricing, and context window.

Current LeaderboardMetric Inventory

Current coding leaderboard

Rankings use the Artificial Analysis coding index. Supporting fields are included only when present in the current dataset.

Additional developer-relevant metrics

Public Artificial Analysis evaluations and methodology, labeled by priority, effort, and current availability in this codebase.

8
Live fields in the leaderboard

Coding, intelligence, benchmarks, pricing, speed, latency, and context.

5
Additional typed fields

Typed locally but not yet shown in the UI.

24
Items needing broader sourcing

Agent, long-context, and workload-specific metrics to source.

First implementation slice

Highest-impact additions based on developer relevance and implementation cost.

Terminal-Bench Hard
Input price per 1M tokens
Output price per 1M tokens
Time to first answer token
Max output tokens
Release date
Coding and agent benchmarks

The most directly useful evaluations for developers choosing models for coding, tool use, long-context work, and agentic execution.

MetricWhat it measuresWhy developers carePriorityEffortStatus
Artificial Analysis Coding IndexArtificial Analysis' aggregate coding ranking.Best single headline score for code-heavy model selection.
High
Low
Live now
LiveCodeBenchFresh competitive-programming code generation and repair tasks.Strong proxy for solving unseen coding problems under execution-based checks.
High
Low
Live now
SciCodeScientist-curated coding tasks from real lab workflows.Useful for research, data, and numerics-heavy coding workflows.
High
Low
Live now
Terminal-Bench HardAgentic work in terminal environments across engineering and ops tasks.Best public signal here for tool use, shell execution, and multi-step agent work.
High
Medium
New source likely
GDPval-AAAgentic task completion on real-world occupation workflows with tools.Useful for ranking full agents, especially browsing and shell-enabled systems.
High
High
New source likely
IFBenchInstruction-following under diverse, verifiable constraints.Good signal for prompt adherence, formatting fidelity, and tool-output compliance.
High
High
New source likely
Artificial Analysis Long Context ReasoningReasoning over long documents from 10k to 100k tokens.Important for repo chat, large specs, logs, and multi-file code review.
High
High
New source likely
tau2-bench TelecomDual-control conversational task execution in support workflows.More support-oriented, but still relevant for agent reliability in constrained workflows.
Medium
High
New source likely