Methodology & Test Environment
To rigorously measure the real-world impact of JevProxy, we deployed an automated benchmark harness across three representative coding agent workflows:
- Refactoring Suite: Modifying 14 React components across a TypeScript repository, verifying tests with Vitest, and formatting with Biome.
2. Debugging Suite: Localizing and fixing an asynchronous race condition in an Express backend across 8 files.
3. Dependency Upgrade Suite: Migrating a Next.js application across major versions, auditing breaking changes, and updating peer dependencies.
Each task was run 100 times across two configurations:
- Baseline: Direct connection to Claude 3.5 Sonnet / GPT-4o via default agent endpoints.
- Accelerated: Direct drop-in with baseURL: https://api.jevproxy.com/v1 using JevProxy edge interception.
BENCHMARK RUNNER TOPOLOGY:
[Agent Suite (Cursor / Claude Code / Codex)]
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+------------+------------+
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[BASELINE] [JEVPROXY]
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Direct Claude 3.5 JevProxy Edge
Avg: 1,420ms / turn Sub-25ms Intercept
$0.0150 / turn $0.0001 / turnKey Findings: Latency
Across all 100 runs per suite, the baseline agent spent an average of 68.4% of total elapsed wall-clock time waiting for model inference on deterministic intermediate turns (e.g., reading files, running git status, listing directory contents).
With JevProxy:
- Median Turn Latency: Dropped from 1,420ms to 18.4ms (77x faster).
- Wall-Clock Completion Time: Decreased by 64.2% on the refactoring suite and 71.8% on the debugging suite.
- Developer Idle Time: Developers experienced near-instantaneous feedback on test executions and file verifications, making the agent feel like an interactive compiler rather than a remote conversational bot.
Key Findings: Cost & Token Savings
Because JevProxy provides 100% Free Output Tokens and charges only $0.0001 per intercepted decision, total session cost dropped by over 91% across all suites.