Real-World Token Economics for RAG Search & Vector Ingestion
RAG workloads are heavily asymmetrical: 95% of token volume is input (retrieved document chunks), with very little generated output.
Typical monthly workload
- Input tokens
- 15,000,000
- Output tokens
- 500,000
- Requests / day
- 2,000
Illustrative estimate. Adjust the sliders below to match your own volume.
Recommended setup
Embed initial chunks with OpenAI embedding ($0.02/M) or bypass chunking entirely by passing full PDF books directly into Gemini 1.5 Pro.
Monthly cost by model for this workload
| Model | Input / 1M | Output / 1M | Est. monthly cost |
|---|---|---|---|
| Gemini 1.5 Flash | $0.075 | $0.30 | $1.27 |
| Gemini 2.0 Flash | $0.100 | $0.40 | $1.70 |
| DeepSeek V3 | $0.140 | $0.28 | $2.24 |
| GPT-4o Mini | $0.150 | $0.60 | $2.55 |
| Qwen 2.5 72B | $0.350 | $0.40 | $5.45 |
| Llama 3.3 70B (Groq/Together) | $0.590 | $0.79 | $9.24 |
| DeepSeek R1 (Reasoning) | $0.550 | $2.19 | $9.35 |
| Claude 3.5 Haiku | $0.800 | $4.00 | $14.00 |
| o3-mini (Reasoning) | $1.100 | $4.40 | $18.70 |
| Gemini 1.5 Pro | $1.250 | $5.00 | $21.25 |
| Mistral Large 2 | $2.000 | $6.00 | $33.00 |
| Grok 2 | $2.000 | $10.00 | $35.00 |
| GPT-4o (Omni) | $2.500 | $10.00 | $42.50 |
| Claude 3.5 Sonnet | $3.000 | $15.00 | $52.50 |
| o1 (Reasoning) | $15.000 | $60.00 | $255.00 |
Computed from list prices and the workload above (15,000,000 input and 500,000 output tokens per month), with no caching or batch discounts. Real bills vary.
How to cut this cost
- Bypass Vector Databases with 2M Context Models
For small enterprise intranets (<200 documents), passing documents directly into Gemini 1.5 Pro eliminates vector DB infrastructure costs completely.
- Apply Reranking Before Synthesis
Use Cohere Rerank to filter 50 retrieved chunks down to the top 3 most relevant before sending to the LLM, cutting input tokens by 80%.
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
How much does it cost to index 1,000 PDF pages?
1,000 standard PDF pages contain roughly 500,000 words (~650,000 tokens). Embedding this volume with OpenAI text-embedding-3-small costs approximately $0.013.