Applied AI · Decision tool · 100% client-side
LLM Cost Decision Engine
The fastest way to estimate and reduce your LLM spend. Side-by-side model comparison, real-world conversation patterns (single-shot, multi-turn, agent, RAG), an inline prompt analyzer that flags token bloat, and budget guardrails that tell you exactly when you blow the budget, and which model to switch to.
Deterministic math. No LLM calls. Your prompt never leaves the browser.
1 · Configure your workload
Single shot. One input → one output. Classification, summarization, function calls.
Recommended for Single shot: ~60%.
Set a target to see green / yellow / red status against your selected model.
Prompt analyzer · heuristic
Estimated savings: ~14 tokens ($0.4200 / month on Claude Sonnet 4.6)
- Politeness phrasing. 2× "please make sure to". Polite hedging adds tokens without changing model behavior. / 30 chars
- Verbose phrasing. 1× "In order to". "In order to" → "to" saves 2 words per occurrence. / 11 chars
- Verbose phrasing. 1× "make sure to". "Make sure to X" → "X" reads the same to the model. / 13 chars
2 · Decision
$23.56 / month on Claude Sonnet 4.6 · 4630% above Gemini 3 Flash
$0.0024 per request · $283 annualized · 64 effective input + 150 output per request after the single shot multiplier.
3 · Compare across all models
Pricing live from LiteLLM · refreshed every 24hSame workload, every major model (15 listed including Kimi K2, DeepSeek V3 + R1, Qwen 3 Max, Grok 4), ranked by total monthly cost. Cheapest highlighted in green; selected highlighted in brass.
Estimate. Token counts use a character-rate heuristic (4 chars/token for english prose); the real provider tokenizer can vary by ±10%. Prices are public list prices, refreshed daily from the LiteLLM model registry (used in production by hundreds of teams). Manual overrides fall back if the registry is unreachable. Excludes negotiated rates, gateway routing fees, or bring-your-own-key savings, verify against your provider's billing dashboard before committing to a budget.
How AI engineers actually use this
- Capacity planning before a launch. Estimate the burn at projected scale before the credit card lands.
- Routing decisions. Compare a frontier model versus a fast-cheap model on the same workload to size the cost-per-quality tradeoff.
- Prompt-caching ROI. Slide the cached fraction up to see how much a stable system prompt + RAG context actually saves at your volume.
- Budget defense. Walk into the budget conversation with a sourced number, not a guess.
Common questions
How accurate is the token estimate?
The calculator uses a character-rate heuristic (4.0 chars per token for English, 3.2 for mixed text + code, 2.4 for code-heavy, 1.6 for non-Latin scripts). Real provider tokenizers vary by about 10%. For a budget plan that is good enough; for a billing reconciliation pull the exact count from your provider's dashboard or run your prompt through tiktoken (OpenAI) or Anthropic's count_tokens endpoint.
Why does prompt caching matter so much?
Anthropic prompt caching documents up to a 90% reduction on cached input tokens (with a one-time 25% surcharge on the initial write). OpenAI prompt caching documents up to a 50% reduction. The cached portion is your stable prefix: system prompt, retrieved context, few-shot examples. The volatile portion is the user's actual input. Putting the stable content first and the volatile content last is what produces the savings.
Why are the prices different from what my provider shows?
These are the published list prices as of April 2026. Negotiated enterprise rates, committed-spend discounts, AI Gateway routing fees, and bring-your-own-key savings will all change the real number. The calculator is for capacity planning, not for billing reconciliation.
Why isn't model X listed?
We list the major frontier and balanced-tier models from OpenAI, Anthropic, Google, Meta, and Mistral. Self-hosted Llama and Mistral on your own GPUs are out of scope because the cost depends on your hardware use. For inference-provider hosted Llama, prices vary by provider (Together, Fireworks, Groq); the calculator uses one representative price for capacity planning.
Does the calculator send my prompt anywhere?
No. The whole calculation runs in your browser. The prompt text is never sent to a DecipherU server, never sent to any AI provider, and never logged. This is a deterministic math tool, not an AI tool.
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