#llm-cost
8 posts tagged with #llm-cost
Every article below is hand-written, technically reviewed, and focused on llm-cost. Posts cover real-world architecture decisions, code-level implementation patterns, and trade-offs you'll only discover after shipping production systems.
Developer Tools OpenAI Decisions API Tutorial [2026]: 3 Cost-Safe Patterns
A production-first OpenAI Decisions API tutorial: typed evals on POST /v1/decisions, predicate/choice/score, and three patterns to gate, batch, and escalate without cost blowups.
Developer Tools How to Measure AI Coding Agent Harness Overhead [2026]
Model wars are a distraction. If you can’t measure prompt scaffolding, repo indexing, context packing, tool calls, and test loops, you’re not benchmarking your coding agent. Here’s a reproducible protocol.
AI and Machine Learning Prompt Compression Token Savings Benchmark [2026]: RTK vs Reality
Token savings are easy to market and hard to bank. Here’s the benchmark framework I trust for RTK-style compression: cost-per-success, tool-call failures, and latency.
AI and Machine Learning Agent Per-Task Cost Calculation [2026]: Retries, Tools, Caching
A spreadsheet-ready expected-cost model for agent workflows that includes retries, tool-call fanout, context growth, and caching. Plus hard budgets you can actually enforce.
Developer Tools AI Agent Cost Per Task [2026]: Token Budgets & Break-Even Math
Concrete per-task cost breakdown for Aider, Claude Code, and OpenHands — covering token overhead per PR, monthly burn at team scale, and the break-even formula for hosted APIs vs local models.
Developer Tools OpenCode vs Claude Code Token Overhead: 4.7x Gap Tested [2026]
Claude Code sends 33,000 tokens before reading your prompt. OpenCode sends 7,000. Here's the cache economics, the multiplier stack, and the break-even math for teams.
AI and Machine Learning Reduce LLM API Costs 60%: 6 Techniques [2026]
A technique-by-technique playbook with real cost math for cutting LLM API bills in production — covering semantic caching, prompt compression, model routing, batch APIs, and context tiering with 2026 pricing.
AI and Machine Learning Gemini 2.5 Flash vs Claude Haiku 4.5: Best Cheap LLM 2026
I'd pick Gemini 2.5 Flash for high-volume document pipelines where cost per token is the primary constraint, and Claude Haiku 4.5 for customer-facing conversational workloads where tone and safety rails matter more than squeezing every fraction of a cent.