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 |
| Gemini 2.0 Flash | $0.100 | $0.40 | $5.40 |
| DeepSeek V3 | $0.140 | $0.28 | $7.28 |
| GPT-4o Mini | $0.150 | $0.60 | $8.10 |
| Qwen 2.5 72B | $0.350 | $0.40 | $17.90 |
| DeepSeek R1 (Reasoning) | $0.550 | $2.19 | $29.69 |
| Llama 3.3 70B (Groq/Together) | $0.590 | $0.79 | $30.29 |
| Claude 3.5 Haiku | $0.800 | $4.00 | $44.00 |
| o3-mini (Reasoning) | $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 |
| Grok 2 | $2.000 | $10.00 | $110.00 |
| 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 scenario or fine-tune token parameters and cloud host below.
Token & Usage ParametersLLM API
Switching from GPT-4o ($195.00/mo) to Gemini 1.5 Flash ($5.85/mo) saves 97%.
Lowest cost per token, high-frequency tasks, real-time audio/video
State-of-the-art open economics, high-performance general intelligence
Real-time conversational streaming, vision, multimodal processing at speed
High-volume text processing, fast chatbots, structured JSON extraction
Top open-weights coding, math, and multilingual benchmark performance
Open-weights privacy, self-hosting or ultra-cheap hosted inferencing
Complex math, algorithmic reasoning, open deep-thinking workflows
Rapid code completion, customer service, fast structured parsing
Cost-effective scientific & coding reasoning, high-accuracy logic
Massive context (2M tokens), full video/audio analysis, large codebases
Multilingual tasks, European compliance, enterprise code generation
Real-time information synthesis, creative generation, vision analysis
Complex multimodal reasoning, coding, and production enterprise apps
Software engineering, nuanced writing, complex agentic tool use
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.