Environmental impact tracking for AI inference providers
{ "service": "InferenceLatency.com", "endpoint": "/efficiency", "timestamp": "2025-09-07T23:20:22.536412Z", "efficiency_analysis": { "providers_analyzed": 7, "most_efficient_provider": "Google Gemini", "least_efficient_provider": "Groq", "average_energy_wh": 0.3486, "average_carbon_g": 0.1115, "grid_carbon_intensity": 320 }, "provider_efficiency": [ { "provider": "Google Gemini", "model": "Gemini-2.0-Flash", "latency_ms": 276, "energy_wh_est": 0.24, "carbon_g_est": 0.0768, "carbon_per_1k_tokens": 76.8, "efficiency_score": 1.51, "grid_gco2_per_kwh": 320, "methodology": "estimated" }, { "provider": "Together AI", "model": "Llama3.1-8B-Turbo", "latency_ms": 262, "energy_wh_est": 0.35, "carbon_g_est": 0.112, "carbon_per_1k_tokens": 112.0, "efficiency_score": 1.09, "grid_gco2_per_kwh": 320, "methodology": "estimated" }, { "provider": "OpenAI", "model": "GPT-4o", "latency_ms": 281, "energy_wh_est": 0.4, "carbon_g_est": 0.128, "carbon_per_1k_tokens": 128.0, "efficiency_score": 0.89, "grid_gco2_per_kwh": 320, "methodology": "estimated" }, { "provider": "Fireworks AI", "model": "Llama3.1-8B", "latency_ms": 368, "energy_wh_est": 0.35, "carbon_g_est": 0.112, "carbon_per_1k_tokens": 112.0, "efficiency_score": 0.78, "grid_gco2_per_kwh": 320, "methodology": "estimated" }, { "provider": "OpenRouter", "model": "Mistral", "latency_ms": 759, "energy_wh_est": 0.35, "carbon_g_est": 0.112, "carbon_per_1k_tokens": 112.0, "efficiency_score": 0.38, "grid_gco2_per_kwh": 320, "methodology": "estimated" }, { "provider": "Claude", "model": "Claude Sonnet 4", "latency_ms": 1366, "energy_wh_est": 0.4, "carbon_g_est": 0.128, "carbon_per_1k_tokens": 128.0, "efficiency_score": 0.18, "grid_gco2_per_kwh": 320, "methodology": "estimated" }, { "provider": "Groq", "model": "llama-3.1-8b-instant", "latency_ms": 2008, "energy_wh_est": 0.35, "carbon_g_est": 0.112, "carbon_per_1k_tokens": 112.0, "efficiency_score": 0.14, "grid_gco2_per_kwh": 320, "methodology": "estimated" } ], "methodology": { "energy_source": "vendor_disclosures_and_estimates", "carbon_calculation": "(energy_wh / 1000) * grid_gco2_per_kwh", "grid_intensity_source": "global_average", "scope": "online_inference_only", "accuracy_note": "Estimates based on available vendor data and industry benchmarks" }, "sustainability_insights": { "greenest_choice": "Google Gemini", "carbon_savings_potential": "Up to 35.2g CO₂e per 1k inferences", "recommendation": "Choose providers with lower energy consumption for high-volume inference workloads" } }