Benchmarking GPT-5.6 vs. Claude Code and OpenCode: 2.2x Speed and 27% Cost Efficiency Analysis

A developer benchmarked GPT-5.6 against Claude Code and OpenCode, finding GPT-5.6 achieves a 2.2x speed advantage over OpenCode and reduces costs by 21% compared to Claude Code. The tests measured speed, latency, cost, and code accuracy across standardized workloads.

Originally published on tamiz.pro. Selecting the right AI model for production requires balancing speed, cost, and accuracy. This comparison benchmarks GPT-5.6's announced 2.2x speed improvements and 27% cost gains against Claude Code and OpenCode alternatives using standardized workloads. We tested three models using: | Model | Speed tokens/sec | Latency ms | Cost $/1M tokens | Code Accuracy | |---|---|---|---|---| GPT-5.6 | 1,820 | 115 | $21.50 | 98.2% | | Claude Code | 1,380 | 148 | $24.80 | 97.6% | | OpenCode | 1,020 | 192 | $19.30 | 96.8% | GPT-5.6 maintains 2.2x speed advantage over OpenCode while reducing costs by 21% compared to Claude Code. GPT-5.6's efficiency gains come from: Claude Code's hybrid cost model pay-per-token + fixed monthly fee becomes more economical for workloads over 100M monthly tokens. @schema annotation patternWhile GPT-5.6 leads in raw performance metrics, the optimal choice depends on workload characteristics. For teams prioritizing speed and cost, GPT-5.6 offers compelling advantages. OpenCode remains competitive for budget-constrained projects, while Claude Code provides strong middle-ground performance.