LLM Reasoning & Token Cost Calculator
Calculate real-world API economics and hardware break-even across frontier models. Factor in prompt cache discounts, Batch API reductions (50%), visible reasoning tokens (CoT), and self-hosted dedicated GPU rental curves.
Cloud API vs Dedicated Hardware Break-Even
At what token scale does renting a dedicated GPU on RunPod / Lambda / Vast.ai beat paying on-demand API tokens? Select your target hardware below:
🔬 Workload Presets & Token Architecture Breakdown
Understand the engineering assumptions behind each preset. Token volumes, reasoning multipliers, and caching dynamics represent real-world 2026 production traffic patterns.
Autonomous Coding Agent (SWE)
Designed for multi-step agent loops (Cursor, Cline, GitHub Copilot Workspace, SWE-bench). Agents ingest codebases, run test suites, and iteratively fix syntax errors.
- • Input (8,000 tok): System prompt, AST schema, file snippets, error logs.
- • Cache Hit (60%): Reusable repo context and static tool definitions.
- • Reasoning (4,500 CoT): Thinking tokens for bug root-cause analysis.
- • Output (1,200 tok): Unified diffs and file rewrite patches.
Customer Support & RAG Bot
High-throughput interactive chatbot integrating vector database embeddings for enterprise help desks, SaaS onboarding, and transactional Q&A.
- • Input (2,500 tok): Knowledge base chunks + user chat history.
- • Cache Hit (75%): Static business policy prompts cached at edge.
- • Reasoning (0 CoT): Instant latency required (<1.5s TTFT).
- • Output (350 tok): Concise, friendly conversational answer.
STEM & Deep Reasoning Pipeline
Specialized evaluation pipeline for complex mathematics, patent law validation, chemical synthesis research, and formal verification tasks.
- • Input (4,000 tok): Dense technical problem statement and constraints.
- • Cache Hit (30%): Lower cache hit due to distinct problem domains.
- • Reasoning (8,000 CoT): Heavy search tree & internal verification steps.
- • Output (2,000 tok): Complete mathematical proofs and step-by-step logic.
Batch Document & PDF Extraction
25,000 calls / mo · High Token DensityAutomated OCR post-processing, multi-page invoice structuring, medical records, and high-volume legal document parsing to strict JSON schemas. Focuses on massive context ingestion without reasoning token inflation.
- • Input (12,000 tok): Large unstructured text, tables, and OCR dump per request.
- • Cache Hit (40%): Reusable extraction schema rules & few-shot examples.
- • Reasoning (0 CoT): Schema compliance priority over multi-step reasoning.
- • Output (800 tok): Deterministic, validated JSON response payload.
📚 Recommended Production Blueprints
Token pricing is only one component of real TCO. Explore our deep dives on agentic loops, failure recovery, and architectural cost caps: