# What it costs to move models, beyond the rate card > Anthropic's newer tokenizer produces about 30% more tokens for the same text. A cost model built on token counts doesn't survive the move. URL: https://getculpa.com/provider-switching-cost Last reviewed: 2026-08-05 Rates effective: 2026-07-02 ## Answer Comparing rate cards is the easy part of a migration and the smallest part of the cost. The same text produces different token counts on different tokenizers, so your volumes change along with your rates. Culpa, a local-first LLM cost, margin, and forecast ledger, prices your real traffic against a versioned price book so both sides move together. ## Why this happens Every migration starts with a rate comparison, and a rate comparison assumes the only thing changing is the price per token. It isn't. Token counts are a property of the tokenizer, not of your text, and Anthropic publishes the clearest illustration of this within its own range: Claude 4.7 and later use a newer tokenizer that produces approximately 30% more tokens for the same text than earlier models. That's a model-family change inside one provider, with the numbers stated. Moving between providers changes the tokenizer too, and none of them publish a comparison, so the honest position is that your volumes will move by an unknown amount and you have to measure it rather than model it. Everything else in a migration compounds that. Prompts tuned for one model rarely transfer unchanged, evaluation has to be re-run to know whether quality held, and any period of dual-running means paying both providers at once for whatever share of traffic you shadow. ## What this usually looks like - Your migration business case compares rates and nothing else. - Nobody has measured what your own prompts tokenize to on the target model. - Prompts were ported unchanged and quality moved in ways nobody priced. - Dual-running was planned and its cost was never added up. - Post-migration spend came in above the rate comparison and nobody can say why. ## Common mistakes - Comparing rate cards and calling it a business case. Why it hurts: Rates are per token and your token count changes with the tokenizer. Do instead: Tokenize a real sample of your own traffic on both models before deciding. - Assuming the same text costs the same tokens. Why it hurts: Anthropic publishes roughly 30% more tokens for identical text across its own model generations. Do instead: Measure your volumes on the target, and re-price at its rates using those volumes. - Leaving dual-running out of the migration cost. Why it hurts: Shadow traffic is paid twice, and migrations run longer than planned. Do instead: Budget the overlap explicitly, at the traffic share and duration you actually expect. - Porting prompts unchanged to save effort. Why it hurts: Prompts tuned for one model produce different output lengths on another, which moves cost as well as quality. Do instead: Re-tune and re-evaluate, and price the output length that comes out of it. ## Self-check - Take a real sample of your traffic and tokenize it on both the current and target model. - Re-price your monthly volume using the target's token counts, not your current ones. - Add the dual-running period at the traffic share you'll actually shadow. - Check whether your prompts assume behaviour specific to the model you're leaving. ## Same text, more tokens (illustrative) Anthropic states that Claude 4.7 and later models use a newer tokenizer producing approximately 30% more tokens for the same text, and that Claude Sonnet 4.6 and earlier use the previous one. Take a modelled 100 million input tokens a month as measured on the older tokenizer, and price the identical text after the shift at Claude Sonnet 5's real introductory rate of $2.00 per million. The volume is modelled, the tokenizer statement and the rate are published. 100M tokens on the older tokenizer: 100M x $2.00/M = $200.00 the same text on the newer tokenizer: approximately 130M tokens 130M x $2.00/M = $260.00 a 30% cost rise from a rate card that never changed at all Nobody changed a price and nothing about the workload moved. A rate comparison would have shown these two as identical. This is within one provider's own range, with the figure published. Across providers the same effect exists and nobody publishes the number, which is the argument for measuring your own traffic rather than modelling it. ## Cost figures Every figure carries its confidence and its source. No figure on this page is provider-reported. - $260.00 against $200.00, modelled monthly cost of identical text before and after a published tokenizer change [calculated] Source: Anthropic's pricing page states that Claude 4.7 and later use a newer tokenizer producing approximately 30% more tokens for the same text, with Claude Sonnet 4.6 and earlier on the previous one. A modelled 100 million input tokens becomes approximately 130 million for identical text, and at Claude Sonnet 5's real introductory rate of $2.00 per million from the price book effective 2026-07-02 gives $200.00 against $260.00. The tokenizer statement and the rate are published, the volume is modelled. ## FAQ Q: Is comparing rate cards enough to plan a migration? A: No, because rates are per token and token counts change with the tokenizer. Anthropic publishes roughly 30% more tokens for the same text between its own model generations, which is a 30% cost move from a rate card that didn't change. Measure your own traffic on the target. Q: How much do token counts differ between models? A: Within Anthropic's range the published figure is approximately 30% more tokens on Claude 4.7 and later than on earlier models, and the exact increase depends on the content. Across providers the same effect exists, no one publishes a comparison, so the only honest answer is to tokenize your own sample. Q: What else does a migration cost? A: Re-tuning prompts, re-running evaluation to confirm quality held, and dual-running. The overlap is the one people forget: shadow traffic is paid to both providers at once, and migrations tend to run longer than the plan allowed for. Q: How do I build a defensible migration case? A: Tokenize a real sample of your traffic on both models, re-price your monthly volume using the target's counts rather than your current ones, and add the dual-run period at the traffic share you'll genuinely shadow. That gives a number you can be held to rather than a rate ratio. ## Sources - Anthropic pricing: https://platform.claude.com/docs/en/docs/about-claude/pricing Run the free Cost Leak Scan: https://app.getculpa.com/scan?source=pseo&slug=provider-switching-cost&cluster=problem Machine-readable index of every guide: https://getculpa.com/api/pages Human-readable index of every guide: https://getculpa.com/guides Site overview: https://app.getculpa.com/llms.txt Privacy: Culpa runs on your infrastructure. Your prompts and responses never leave it. Culpa counts calls to run your plan, and it fails open, so if it ever breaks your app keeps running.