310491a557
- Updated python_coding_microproject.csv to use NVIDIA NIM Kimi K2 - Updated kali_linux_shell_simulator.csv to use NVIDIA NIM Kimi K2 - Made more general-purpose (flexible targets, expanded tools) - Added nemotron-mini-agent.csv for fast local inference via Ollama - Added nemotron-agent.csv for advanced reasoning via Ollama - Added wiki page: Projects for NVIDIA NIMs and Nemotron
32 lines
1.2 KiB
SQL
32 lines
1.2 KiB
SQL
-- Migration 017: Fix Compound model pricing with correct blended rates
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-- Source: https://groq.com/pricing (Dec 2025) + actual API response analysis
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--
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-- Compound uses GPT-OSS-120B ($0.15/$0.60) + Llama 4 Scout ($0.11/$0.34)
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-- Blended 50/50: ($0.15+$0.11)/2 = $0.13 input, ($0.60+$0.34)/2 = $0.47 output
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--
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-- Compound Mini uses GPT-OSS-120B ($0.15/$0.60) + Llama 3.3 70B ($0.59/$0.79)
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-- Blended 50/50: ($0.15+$0.59)/2 = $0.37 input, ($0.60+$0.79)/2 = $0.695 output
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-- Fix Compound pricing (was incorrectly set to $2.50/$6.00)
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UPDATE model_configs
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SET cost_per_million_input = 0.13,
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cost_per_million_output = 0.47,
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updated_at = NOW()
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WHERE provider = 'groq'
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AND model_id LIKE '%compound%'
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AND model_id NOT LIKE '%mini%';
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-- Fix Compound Mini pricing (was incorrectly set to $1.00/$2.50)
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UPDATE model_configs
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SET cost_per_million_input = 0.37,
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cost_per_million_output = 0.695,
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updated_at = NOW()
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WHERE provider = 'groq'
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AND model_id LIKE '%compound-mini%';
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-- Report updated pricing
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SELECT model_id, name, cost_per_million_input as input_per_1m, cost_per_million_output as output_per_1m
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FROM model_configs
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WHERE provider = 'groq' AND model_id LIKE '%compound%'
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ORDER BY model_id;
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