What a Natural-Language-to-SQL Assistant Costs to Run
Text-to-SQL prompts are input-heavy: the database schema and a few example queries are sent with every question, while the generated SQL is short.
Typical monthly workload
- Input tokens
- 4,000,000
- Output tokens
- 600,000
- Requests / day
- 800
Illustrative estimate. Adjust the sliders below to match your own volume.
Recommended setup
Send straightforward single-table questions to GPT-4o Mini and escalate multi-join or window-function queries to Claude 3.5 Sonnet when validation fails.
Monthly cost by model for this workload
| Model | Input / 1M | Output / 1M | Est. monthly cost |
|---|---|---|---|
| Gemini 1.5 Flash | $0.075 | $0.30 | $0.48 |
| Gemini 2.0 Flash | $0.100 | $0.40 | $0.64 |
| DeepSeek V3 | $0.140 | $0.28 | $0.73 |
| GPT-4o Mini | $0.150 | $0.60 | $0.96 |
| Qwen 2.5 72B | $0.350 | $0.40 | $1.64 |
| Llama 3.3 70B (Groq/Together) | $0.590 | $0.79 | $2.83 |
| DeepSeek R1 (Reasoning) | $0.550 | $2.19 | $3.51 |
| Claude 3.5 Haiku | $0.800 | $4.00 | $5.60 |
| o3-mini (Reasoning) | $1.100 | $4.40 | $7.04 |
| Gemini 1.5 Pro | $1.250 | $5.00 | $8.00 |
| Mistral Large 2 | $2.000 | $6.00 | $11.60 |
| Grok 2 | $2.000 | $10.00 | $14.00 |
| GPT-4o (Omni) | $2.500 | $10.00 | $16.00 |
| Claude 3.5 Sonnet | $3.000 | $15.00 | $21.00 |
| o1 (Reasoning) | $15.000 | $60.00 | $96.00 |
Computed from list prices and the workload above (4,000,000 input and 600,000 output tokens per month), with no caching or batch discounts. Real bills vary.
How to cut this cost
- Send only relevant tables
Retrieve the 3 to 5 tables that match the question instead of the entire schema to shrink every prompt.
- Validate before escalating
Run EXPLAIN on the generated SQL. Only retry on the stronger model when the query fails, so most requests stay on the cheap tier.
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
Why is the schema the biggest cost in Text-to-SQL?
The schema is resent with every request, so a 2,000-token schema dominates the bill when answers are only 100 to 200 tokens. Prompt caching or table retrieval cuts this directly.