LLM API Migration Savings Calculator
Prices verified 2026-07-14 against official provider pricing pages. Methodology and formula: how these numbers are computed.
Quick answer: for a typical customer-support workload (100K conversations/month, 60% prompt-cache hit rate), switching from OpenAI GPT-5.6 Sol ($2,352/month) to DeepSeek V4 Flash ($30.64/month) reduces LLM API spend by 99%. Savings for your workload depend on token mix, cache hit rate and quality requirements — enter your numbers below.
Your workload
Current API prices (USD per 1M tokens, verified 2026-07-14)
| Model | Input | Cached input | Output | Batch discount | Context |
|---|---|---|---|---|---|
| OpenAI GPT-5.6 Sol | $5.00 | $0.50 | $30.00 | 50% | 1M |
| OpenAI GPT-5.6 Terra | $2.50 | $0.25 | $15.00 | 50% | 1M |
| OpenAI GPT-5.6 Luna | $1.00 | $0.10 | $6.00 | 50% | 1M |
| Anthropic Claude Fable 5 | $10.00 | $1.00 | $50.00 | 50% | 1M |
| Anthropic Claude Opus 4.8 | $5.00 | $0.50 | $25.00 | 50% | 1M |
| Anthropic Claude Sonnet 5 | $2.00 | $0.20 | $10.00 | 50% | 1M |
| Anthropic Claude Sonnet 4.6 | $3.00 | $0.30 | $15.00 | 50% | 1M |
| Anthropic Claude Haiku 4.5 | $1.00 | $0.10 | $5.00 | 50% | 200K |
| DeepSeek DeepSeek V4 Pro | $0.43 | $0.0036 | $0.87 | — | 1M |
| DeepSeek DeepSeek V4 Flash | $0.14 | $0.0028 | $0.28 | — | 1M |
| Google Gemini 3.1 Pro | $2.00 | $0.20 | $12.00 | 50% | 1M |
| Google Gemini 3.5 Flash | $1.50 | $0.15 | $9.00 | 50% | 1M |
| Google Gemini 3.1 Flash-Lite | $0.25 | $0.03 | $1.50 | 50% | 1M |
Sources: OpenAI pricing · Anthropic pricing · DeepSeek pricing · Gemini API pricing. Model-specific caveats (long-context surcharges, cache-write fees, introductory pricing) are listed in the methodology.
Worked examples
Three common workload shapes, computed with the same formula as the calculator. Negative savings means the alternative is more expensive than the baseline.
Customer-support chatbot — baseline OpenAI GPT-5.6 Sol at $2,352/month
100,000 conversations/month, 2 LLM calls per conversation, 1,200 input / 300 output tokens per call, 60% prompt-cache hit rate, real-time (no batch).
| Switch to | Monthly cost | Savings | Savings % |
|---|---|---|---|
| DeepSeek DeepSeek V4 Flash | $30.64 | $2,321 | 99% |
| DeepSeek DeepSeek V4 Pro | $94.48 | $2,258 | 96% |
| Google Gemini 3.1 Flash-Lite | $118 | $2,234 | 95% |
| Anthropic Claude Haiku 4.5 | $410 | $1,942 | 83% |
| OpenAI GPT-5.6 Luna | $470 | $1,882 | 80% |
| Google Gemini 3.5 Flash | $706 | $1,646 | 70% |
RAG-powered SaaS feature — baseline OpenAI GPT-5.6 Terra at $10,275/month
1,000,000 requests/month, 1 call per request, 3,000 input / 500 output tokens (retrieved context dominates input), 70% cache hit rate, real-time.
| Switch to | Monthly cost | Savings | Savings % |
|---|---|---|---|
| DeepSeek DeepSeek V4 Flash | $272 | $10,003 | 97% |
| DeepSeek DeepSeek V4 Pro | $834 | $9,441 | 92% |
| Google Gemini 3.1 Flash-Lite | $1,028 | $9,248 | 90% |
| Anthropic Claude Haiku 4.5 | $3,610 | $6,665 | 65% |
| OpenAI GPT-5.6 Luna | $4,110 | $6,165 | 60% |
| Google Gemini 3.5 Flash | $6,165 | $4,110 | 40% |
Overnight document pipeline — baseline Anthropic Claude Sonnet 4.6 at $20,760/month
2,000,000 documents/month, 1 call per document, 4,000 input / 800 output tokens, 30% cache hit rate, batch API enabled.
| Switch to | Monthly cost | Savings | Savings % |
|---|---|---|---|
| DeepSeek DeepSeek V4 Flash | $1,239 | $19,521 | 94% |
| Google Gemini 3.1 Flash-Lite | $1,930 | $18,830 | 91% |
| DeepSeek DeepSeek V4 Pro | $3,837 | $16,923 | 82% |
| Anthropic Claude Haiku 4.5 | $6,920 | $13,840 | 67% |
| OpenAI GPT-5.6 Luna | $7,720 | $13,040 | 63% |
| Google Gemini 3.5 Flash | $11,580 | $9,180 | 44% |
Frequently asked questions
How much can I save by switching from OpenAI GPT-5.6 Sol to DeepSeek V4?
For a typical customer-support workload (100K conversations/month, 60% cache hit rate), switching from GPT-5.6 Sol ($2,352/month) to DeepSeek V4 Flash ($30.64/month) cuts LLM API spend by 99%. DeepSeek V4 Flash lists at $0.14/1M input and $0.28/1M output tokens versus GPT-5.6 Sol at $5.00/1M input and $30.00/1M output (prices verified 2026-07-14). Actual savings depend on your input/output token mix, cache hit rate and quality requirements — use the calculator above with your own numbers.
Do batch API discounts stack with prompt caching?
On Anthropic, yes: a cached read inside a batch request is billed at 50% of the 10% cache-read rate, i.e. 5% of the standard input price — up to 95% off input tokens. OpenAI and Google also apply their 50% batch discount on top of cached-input rates. DeepSeek has no batch API and instead relies on automatic caching with a ~98-99% cache-read discount and no cache-write or storage fees.
Is the DeepSeek API compatible with the OpenAI SDK?
Yes. DeepSeek V4 exposes both OpenAI-compatible and Anthropic-compatible endpoints, so most migrations only require changing the base URL, API key and model name. Note that the legacy deepseek-chat and deepseek-reasoner aliases are scheduled for deprecation on 2026-07-24 — target the V4 model names directly.
What hidden costs should I check before switching LLM providers?
Four things routinely eat into headline savings: (1) quality regression — run your own eval set before and after, cheaper models can raise retry and human-escalation rates; (2) cache architecture differences — Anthropic charges cache writes (1.25-2x input price) and Google charges cache storage per hour, so cache-heavy workloads do not transfer 1:1; (3) rate limits and latency SLOs on the cheaper tier; (4) data-residency and compliance requirements, which may rule providers out regardless of price.
Why do AI agents cost more than the per-token price suggests?
One user request to an agent typically triggers 3-10 internal LLM calls (planning, tool calls, validation), and each step re-sends accumulated context. Multiply your expected per-request cost by the agent chain depth — the calculator has a "calls per request" field for exactly this.