LLM Token & GPU VRAM Cost Calculator
Interactive 2026 multi-model API pricing comparison, token budget estimator, and GPU hardware VRAM sizing calculator for local and cloud inference.
[ PARAMETERS ] Token Workload
2,000 tokens
500 tokens
1,000 req/day
[ ESTIMATED COST ] Pricing Output
Monthly Estimated Cost
$405.00
Cost / Single Request
$0.01350
Cost / 1,000 Requests
$13.50
Daily Token Volume
2.5M Tok
[ NOTE ] Prompt Caching Benefit: For models supporting prompt caching (Anthropic, DeepSeek, Google), cache-hit tokens typically yield 75% to 90% discount on input pricing.
[ BENCHMARK ] Multi-Model Cost Matrix (Monthly at Selected Volume)
| Model | Provider | Input $/1M | Output $/1M | Cost / Req | Monthly Cost |
|---|
[ ARCHITECTURE ] Model & KV-Cache Configuration
32,768 tokens
4 concurrent streams
[ HARDWARE SPEC ] Required VRAM & Sizing
Total VRAM Required
7.8 GB
Model Weights VRAM
4.0 GB
KV-Cache Memory
2.3 GB
CUDA Context & Overhead
1.5 GB
Recommended GPU Hardware Tier:
1x RTX 4060 Ti 16GB / Apple M3 24GB
[ SIZING FORMULA ]: Total VRAM = (Weights_GB) + (2 × n_layers × n_kv_heads × d_head × seq_len × batch_size × kv_bytes) + CUDA_Context_Buffer.
[ INTERACTIVE ] In-Browser Subword Token Boundary Highlighter
Type or paste any prompt below to visualize subword splitting, token boundaries, and approximate token counts in real-time.
Tokens: 23
Characters: 149
Bytes: 149 B
Avg Chars/Token: 6.5
Visualized Token Chunks: