Claude Opus 4.6 vs Claude Opus 4.6 (Fast)

The 'Fast' variant trades a 6% performance drop (62/100 vs 66/100) for significantly lower latency, which can be critical for real-time coding assistants or interactive development environments. At $30/M input tokens (6x standard), you're essentially paying $25 extra per million tokens for speed optimization while maintaining the same 1M context window and 128K max output.

Standard Claude Opus 4.6 would cost $2.50 for input plus approximately $3.13 for a 125K token analysis output (totaling $5.63), while the Fast variant would charge $15 input plus $18.75 output for $33.75 total. The 6x price multiplier means you're paying an extra $28.12 per large codebase analysis for faster response times.

The Fast variant likely uses aggressive optimization techniques like quantization or pruning to achieve lower latency, resulting in the 62/100 score versus 66/100 for the standard model. This suggests the speed optimizations introduce roughly 6% accuracy degradation on coding tasks, despite maintaining the full 1M token context and all capabilities including vision and function calling.

Assuming a 70/30 input/output split, the standard model would cost $1,050/month ($350 input + $700 output), while Fast would run $6,300/month ($2,100 input + $4,200 output). The $5,250 monthly premium for Fast processing 300M tokens means you're paying $17.50 per million tokens extra for reduced latency.