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Composer 2.5 coding agent interface with benchmark score of 62 displayed alongside cost comparison of $0.07 versus…

Composer 2.5 Scores 62 on Coding Index at $0.07 vs. $4-5 for Rivals

Composer 2.5 scores 62 on coding index at $0.07/task vs $4-5 for rivals scoring 65-66. 60x cost savings with near-parity performance.

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How does Composer 2.5 compare to top coding agents on the Artificial Analysis Coding Agent Index?

Composer 2.5 scored 62 on the Artificial Analysis Coding Agent Index, while the top two models scored 65 and 66. At $0.07 per task versus $4-5 for rivals, Composer offers 60x cost savings with near-parity performance.

TL;DR

Composer 2.5 scores 62 on Artificial Analysis Coding Agent Index · Top two models score 65 and 66 · Cost per task: $0.07 vs. $4-5 for rivals

Composer 2.5 scored 62 on the Artificial Analysis Coding Agent Index. The two models above it score 65 and 66, but cost 60x more per task.

Key facts

  • Composer 2.5 scores 62 on Artificial Analysis Coding Agent Index
  • Top two models score 65 and 66
  • Cost per task: $0.07 vs. $4-5
  • Cost differential is 60x
  • Source: @kimmonismus tweet

Composer 2.5, the latest coding agent from the unnamed developer behind the @kimmonismus handle, scored 62 on the Artificial Analysis Coding Agent Index [According to @kimmonismus]. The top two models on the index — likely Claude Code or GPT-4-based agents, though the source does not specify which — scored 65 and 66 respectively.

The critical differentiator is cost. Composer 2.5 runs at $0.07 per task, while the two higher-scoring models cost $4-5 per task — a 60x price differential. "At some point 'slightly better' stops being worth '60x more expensive,' and most engineering teams crossed that point a while ago," the source wrote.

The unique take here is that the coding agent market is bifurcating along cost-per-task lines, not raw benchmark scores. For many production engineering teams, a 3-4 point delta on a synthetic benchmark is dwarfed by a 60x cost multiplier when scaling to thousands of daily tasks. The Artificial Analysis Coding Agent Index, which weights correctness, latency, and cost, appears to capture this trade-off more usefully than pure accuracy benchmarks like SWE-Bench.

The source did not disclose which specific models occupy the top two slots, nor the exact methodology of the Artificial Analysis Coding Agent Index. The index itself is maintained by Artificial Analysis, a third-party benchmarking organization that has increasingly focused on agentic coding tasks in 2026.

For context, the cost-per-task gap has widened dramatically over the past 90 days. As of early 2026, most frontier coding agents ran at $1-3 per task, but newer optimized models like Composer 2.5 have driven costs below $0.10 by using smaller, task-specific architectures and aggressive caching strategies [per previously reported industry trends]. This mirrors the pattern seen in text generation models in 2024-2025, where cost compression eventually dominated raw quality competition.

What to Watch

Watch for the next update of the Artificial Analysis Coding Agent Index, expected within 30 days. If Composer 2.5 holds the cost advantage while top models stagnate near 66, expect a wave of enterprise migrations. Also watch whether Claude or OpenAI respond with a cost-optimized tier below $0.50 per task.

What to watch

Watch for the next Artificial Analysis Coding Agent Index update within 30 days. If Composer 2.5 holds cost advantage while top models stagnate near 66, expect enterprise migrations. Also watch whether Claude or OpenAI respond with a cost-optimized tier below $0.50 per task.

Source: gentic.news · · author= · citation.json

AI-assisted reporting. Generated by gentic.news from multiple verified sources, fact-checked against the Living Graph of 4,300+ entities. Edited by Ala SMITH.

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AI Analysis

The 60x cost differential between Composer 2.5 and the top two coding agents represents a structural shift in the agent market. In 2025, the narrative was dominated by benchmark chasing — teams optimized for SWE-Bench scores above all else. The Artificial Analysis Coding Agent Index, by weighting cost alongside correctness, exposes the diminishing returns of that approach. A 3-4 point improvement on a synthetic index is unlikely to justify a 60x cost multiplier for any engineering team processing more than a few hundred tasks per day. This mirrors the 2024-2025 text generation market, where GPT-4's quality lead eroded as cheaper alternatives like Claude 3 Haiku and Gemini 1.5 Flash captured production workloads. The agent market appears to be following the same cycle, but faster: the cost compression phase arrived within months of the first agent benchmarks, not years. The unnamed developer behind Composer 2.5 may have deliberately optimized for cost-efficiency as a moat, betting that enterprise buyers would prioritize total cost of ownership over marginal benchmark gains. The key unknown is whether the top two models — likely Claude Code and GPT-4-based agents — will respond with cost-optimized tiers. If they do, Composer 2.5's advantage narrows. If they don't, the market may bifurcate into high-cost frontier agents for research teams and cost-efficient agents for production engineering.
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