LLM Cost for Summarizing Logs and Incidents
Raw logs are enormous. Sending them unfiltered is the fastest way to a large bill, so filtering comes first.
Typical monthly workload
- Input tokens
- 50,000,000
- Output tokens
- 1,000,000
- Requests / day
- 300
Illustrative estimate. Adjust the sliders below to match your own volume.
Recommended setup
Filter and deduplicate logs locally, then send only error clusters to the model for explanation.
Monthly cost by model for this workload
| Model | Input / 1M | Output / 1M | Est. monthly cost |
|---|---|---|---|
| Gemini 1.5 Flash | $0.075 | $0.30 | $4.05 |
| DeepSeek V3 / V2.5 | $0.140 | $0.28 | $7.28 |
| GPT-4o Mini | $0.150 | $0.60 | $8.10 |
| Llama 3.3 70B (Groq/Together) | $0.590 | $0.79 | $30.29 |
| Claude 3.5 Haiku | $0.800 | $4.00 | $44.00 |
| o1-mini | $1.100 | $4.40 | $59.40 |
| Gemini 1.5 Pro | $1.250 | $5.00 | $67.50 |
| Mistral Large 2 | $2.000 | $6.00 | $106.00 |
| GPT-4o (Omni) | $2.500 | $10.00 | $135.00 |
| Claude 3.5 Sonnet | $3.000 | $15.00 | $165.00 |
| o1 (Reasoning) | $15.000 | $60.00 | $810.00 |
Computed from list prices and the workload above (50,000,000 input and 1,000,000 output tokens per month), with no caching or batch discounts. Real bills vary.
How to cut this cost
- Cluster before prompting
Group identical stack traces and send one example with a count.
- Redact secrets
Mask tokens, keys and personal data before any log leaves your network.
Simulate your own spend
Quick Workload Presets
Pick a ready-made scenario or customize your token volume below.
Token & Usage Parameters
By switching or routing background tasks from GPT-4o to Gemini 1.5 Flash, your team saves up to $2,270 annually.
Lowest cost per token, high-frequency tasks, real-time audio/video
State-of-the-art open economics, high-performance general intelligence
High-volume text processing, fast chatbots, classification
Open-weights privacy, self-hosting or ultra-cheap hosted inferencing
Rapid code completion, customer service, structured data extraction
Fast STEM reasoning, competitive programming at lower cost
Massive context (2M tokens), full video/audio analysis, large codebases
Multilingual tasks, European compliance, enterprise code generation
Complex multimodal reasoning, coding, and production apps
Software engineering, nuanced writing, complex agentic workflows
Advanced mathematics, algorithmic coding, PhD-level scientific logic
Frequently asked questions
Should I send raw logs to an LLM?
Avoid it. Filter, deduplicate and redact first; this cuts cost sharply and reduces the risk of leaking secrets.