Quantifying Token Depletion: A Comparative Benchmark of $20 AI Subscription Usage Limits across Claude, Codex, and Cursor

In the current landscape of Large Language Model (LLM) integration into developer workflows, the primary metric for evaluating cost-efficiency is often cited as API pricing—specifically, the cost per million input and output tokens. However, for the majority of professional developers utilizing managed environments like Claude Code, Codex, or Cursor, the more critical bottleneck is not the raw API cost, but the exhaustion of subscription-based usage quotas. These quotas manifest as five-scale hour limits, weekly windows, and monthly caps.

This technical report details an experimental evaluation designed to measure the "subsidization" efficiency of three $20/month subscriptions. By executing a standardized set of ten high-complexity coding prompts across different model architectures, we aim to determine which subscription plan depletes its allocated usage windows most aggressively and which provides the highest quality-to-quota ratio.

Experimental Methodology: The "Apples-to-Apples" Framework

To ensure statistical significance and eliminate variables such as context caching or prompt-specific optimization, the experiment was conducted under a strict controlled environment:

1. Standardized Prompt Set: Ten identical prompts were utilized across all tested models. These prompts were derived from an established coding leaderboard to ensure high difficulty.
2. Target Environment: The test cases focused on two specific PHP/Laravel projects:
   • Hardening a synchronization API.
   • Hardening a contact CSV importer.
3. Complexity Focus: Both tasks required the validation of existing code, necessitating deep semantic understanding and structural analysis.
4. Zero-Cache Execution: The evaluation script was configured to run via CLI (Claude CLI/Cursor CLI) with no prior caching enabled. This ensures that every prompt represents a "cold start" for the model's context window, accurately reflecting real-world usage of new tasks.
5. Metric Tracking: We monitored three primary vectors:
   • Quota Depletion: Percentage change in 5-hour, weekly, and monthly limits.
   • Inference Latency/Duration: Total execution time for the 10-prompt batch.
   • Functional Accuracy: Pass/fail rates of the automated test suites within the PHP projects.

Analysis of Anthropic Claude Code: Opus 5.5 vs. Sonnet 5.5

The first phase of testing focused on the Anthropic ecosystem, specifically comparing the high-reasoning capabilities of Opus 5.5 against the efficiency-oriented Sonnet 5.5.

Opus 5.5 (Medium Effort)

Running Opus 5.5 at a "medium" effort level yielded exceptional functional accuracy, with a 100% pass rate across all 41 tests in Project A and 29 tests in Project B. However, the impact on the subscription quota was significant:

• 5-Hour Limit Depletion: Increased from 7% to 48% (a 41% delta).
• Weekly Limit Depletion: Increased from 28% to 32% (a 4% delta).
• Total Execution Cost/Time: The batch took approximately 27 minutes, with an API-equivalent cost of $6.96.

Sonnet 5.5 (High Effort)

To test the limits of a more "economical" model, we utilized Sonnet 5.5 on a "high effort" configuration. While this setting is intended to bridge the reasoning gap between Sonnet and Opus, it introduced notable regressions in reliability:

• 5-Hour Limit Depletion: Increased from 7% to 75% (a 68% delta).
• Weekly Limit Depletion: Increased from 34% to 34% (negligible change).
• Accuracy Degradation: Unlike Opus, Sonnet failed several tests within the validation suite, demonstrating that while "high effort" settings mitigate some reasoning gaps, they do not eliminate them.

The data suggests that while Sonnet is more aggressive in consuming the short-term 5-hour window, both models impact the weekly quota at roughly similar rates (~4%).

Codex Evaluation: GPT 6.1 Sol (Medium Level)

Next, we transitioned to the Codex environment using GPT 6.1 Sol at a medium level of reasoning. This model was evaluated for its ability to maintain high-quality code generation under heavy load.

The results indicated that while GPT 6.1 Sol is highly capable—maintaining a perfect pass rate across all tests—it suffers from significant latency issues, particularly during periods of high server demand (noted as being slower during late-night execution).

• 5-Hour Limit Depletion: The usage dropped from 93% to 68% remaining (a ~25% delta).
• Weekly Limit Depletion: Decreased from 90% to 86% remaining (a 4% delta).

Interestingly, the depletion of the weekly quota for GPT 6.1 Sol was significantly lower than that of Claude's models (~4% vs ~4%), suggesting a more efficient utilization of the weekly window despite the increased latency in some runs.

Cursor and Grok: The Monthly Paradigm

The final test involved Cursor using the Grok 4.6 model (High Effort, No Fast Mode). Unlike Claude or Codex, Cursor operates on a monthly usage paradigm for its proprietary models.

This test was characterized by extreme latency; the execution of just ten prompts took over one hour. Furthermore, the quality metrics were inconsistent, with several failures in both the synchronization API and CSV importer projects.

• Monthly Limit Depletion: Increased from 12% to only 14% (a mere 2% delta).

While Grok 4.6 is remarkably "cheap" in terms of monthly quota consumption, the trade-off involves significantly higher latency and lower reliability compared to the Anthropic or Codex alternatives.

Synthesis and Conclusion: The Economics of Subsidization

When comparing these $20/month plans, we must distinguish between short-term throughput (5-hour window) and long-term sustainability (weekly/monthly windows).

The primary takeaway is that for developers performing intensive, high-frequency coding sessions, the 5-hour window is the critical bottleneck. Claude Opus 5.5 provides unparalleled accuracy but can exhaust a 5-hour quota in a single session of moderate complexity. Conversely, if your workflow involves long-running, asynchronous tasks where latency is secondary to quota preservation, models like GPT 6.1 Sol or Grok 4.6 offer superior weekly/monthly stability.

Ultimately, the choice between these subscriptions depends on whether your development bottleneck is reasoning accuracy (favoring Opus) or quota longevity (favoring Codex or Cursor).