Claude Cost Calculator

Estimate your monthly Anthropic API costs. See how Claude Fable, Opus, Sonnet and Haiku compare to GPT, Gemini and others.

Anthropic cheapest option: Claude Haiku 5.5 at U$ 5.50/mo โ€” overall cheapest is GPT-6 Luna (U$ 5.50/mo)

Anthropic Models

ModelPer RequestMonthly Total
bestClaude Haiku 5.5U$ 0.000550U$ 5.50
Claude Haiku 4.5U$ 0.0055U$ 55.00
Claude Sonnet 5.5U$ 0.0110U$ 110
Claude Sonnet 5U$ 0.0110U$ 110
Claude Opus 5.5U$ 0.0220U$ 220
Claude Opus 5U$ 0.0275U$ 275
Claude Fable 5.1U$ 0.0550U$ 550

All Models (Comparison)

ModelPer RequestMonthly Total
bestGPT-6 LunaU$ 0.000550U$ 5.50
Claude Haiku 5.5U$ 0.000550U$ 5.50
Llama 4 MaverickU$ 0.000700U$ 7.00
GPT-5.6 LunaU$ 0.0013U$ 13.00
Nemotron 3 UltraU$ 0.0024U$ 24.50
Gemini 3.8 FlashU$ 0.0041U$ 41.25
GLM-5.2U$ 0.0051U$ 51.00
Claude Haiku 4.5U$ 0.0055U$ 55.00
GPT-6.1 SolU$ 0.0110U$ 110
Claude Sonnet 5.5U$ 0.0110U$ 110
Claude Sonnet 5U$ 0.0110U$ 110
Gemini 4 ArgonU$ 0.0110U$ 110
GPT-5.6 TerraU$ 0.0130U$ 130
Gemini 3.1 Pro PreviewU$ 0.0130U$ 130
Kimi K3U$ 0.0165U$ 165
GPT-5.6 SolU$ 0.0220U$ 220
Claude Opus 5.5U$ 0.0220U$ 220
Claude Opus 5U$ 0.0275U$ 275
GPT-6 AstraU$ 0.0550U$ 550
Claude Fable 5.1U$ 0.0550U$ 550

How Anthropic API pricing works

Anthropic prices Claude models per million tokens, split between input and output, and โ€” like most providers โ€” output tokens cost more than input tokens because generation is more compute-intensive than reading. This calculator multiplies your average input and output tokens per request by Claude's current per-model rate, then scales by your expected monthly request volume. Anthropic also offers prompt caching, which can cut the cost of repeated system prompts or long context by a large margin on cache hits, plus batch processing for asynchronous jobs at a further discount โ€” neither is applied here, so this is a full-price, worst-case estimate.

Picking the right Claude tier for the job

Anthropic sells capability in tiers, and the price gaps between them are large enough to decide your architecture. Haiku is built for high-volume, well-defined tasks โ€” classification, extraction, routing, short answers โ€” where its per-token rate is a small fraction of the larger models'. Sonnet is the workhorse tier for reasoning-heavy work like coding, analysis and long-form writing. The practical question is rarely "which model is best" but "what is the cheapest tier that clears my quality bar", and the honest way to answer it is to run your own test set through each tier and compare failures, not vibes.

A useful mental model: if a task can be described completely in the prompt โ€” fixed format, clear rules, no judgment calls โ€” it probably belongs on Haiku. The moment a task needs the model to weigh trade-offs or hold a long chain of reasoning, budget for Sonnet rates in your estimate above.

The economics of prompt caching

Prompt caching is Anthropic's most underused discount. You pay a small premium to write a prompt prefix into the cache, and subsequent requests that reuse that exact prefix read it at a large discount โ€” roughly an order of magnitude cheaper than regular input. The catch is the cache lifetime: entries expire after a few minutes of inactivity, so the discount only materializes when requests arrive close together.

That shape fits three workloads almost perfectly: chatbots with a large system prompt serving steady traffic, RAG applications that pin the same reference context across many questions, and agents that repeatedly re-read the same documents in one session. If your traffic is sparse โ€” a request every ten minutes โ€” cache entries expire between calls and the write premium becomes pure overhead. Estimate with the full-price number from the calculator above, then treat caching as an optimization to validate with real traffic.

Claude-specific budgeting tips

Three habits keep Anthropic invoices predictable. Set max_tokens deliberately โ€” it is a hard cost ceiling per request, and generous defaults quietly permit expensive answers. Watch conversation length: Claude's large context window makes it easy to carry an entire session's history in every request, and all of it is billed as input each turn. And route asynchronous work through the Batch API, which cuts the price of jobs that can tolerate delay roughly in half.

To sanity-check whether Claude is the right home for your workload at all, run the same numbers through the OpenAI cost calculator and the GPT vs Claude comparison โ€” the winner often changes with the input/output ratio. For a full head-to-head with tier mapping and caching differences, read Claude Sonnet 5 vs GPT-5.6: a fair cost comparison.

Claude next to the alternatives, tier by tier

Anthropic's current line-up has four tiers, all with a 1M-token context window, per million tokens (input / output): Claude Fable 5.1 at $10.00 / $50.00, Opus 5.5 at $4.00 / $20.00, Sonnet 5.5 at $2.00 / $10.00 and Haiku 5.5 at $0.10 / $0.50. Opus 5.5 is 20% cheaper than Opus 5 ($5.00 / $25.00), Sonnet 5.5 keeps the price of Sonnet 5 but halves cache reads to $0.10, and Haiku 5.5 costs a tenth of Haiku 4.5 ($1.00 / $5.00, 200k window). The previous models stay in the calculator so you can compare. Haiku 5.5 has one catch: prompts over 100K tokens are billed at $0.50 / $2.50.

OpenAI now matches Claude almost tier for tier: GPT-6 Astra at $10.00 / $50.00 equals Fable, GPT-6.1 Sol at $2.00 / $10.00 equals Sonnet and GPT-6 Luna at $0.10 / $0.50 equals Haiku, while the older GPT-5.6 Sol ($4.00 / $20.00) costs the same as Opus 5.5. With identical list prices, what separates the two is long prompts: Fable, Opus and Sonnet charge a flat rate across the full window, whereas GPT-6 doubles the input rate above 272K tokens and Haiku 5.5 jumps above 100K. Outside the two, Kimi K3 ($3.00 / $15.00) now costs more than Sonnet 5.5, and GLM-5.2 ($1.40 / $4.40) undercuts Sonnet but not Haiku 5.5. The tier-by-tier guide goes deeper on picking between them.

Three real Claude workloads, priced

A customer support assistant. A 1,200-token system prompt plus 300 tokens of user message, answering in about 250 tokens, run 20,000 times a month โ€” roughly 30M input and 5M output tokens. On Haiku 5.5 that is about $3 in and $2.50 out: $5.50 a month, against $55 on Haiku 4.5. The same volume on Opus 5.5 costs about $120 in and $100 out: $220, forty times more for a task Haiku usually handles fine.

A document summarizer. A 40k-token report in, a 1,500-token summary out, 200 documents a month. Sonnet 5.5: 8M input tokens ($16) and 300k output ($3), so about $19 โ€” the same as Sonnet 5, since the list price did not change. On Haiku 5.5 the same job costs under $1, because each 40k-token prompt stays below the 100K threshold. Our PDF summary calculator models this shape in more detail.

A coding agent. These are output-heavy and iterate: 15k in, 4k out, 500 runs a month. On Sonnet 5.5 that is 7.5M input ($15) and 2M output ($20) โ€” about $35; on Opus 5.5, $70. Cache the parts of the prompt that repeat and the input side drops by 90โ€“95%: cache reads cost 5% of the input rate on Opus 5.5 and Sonnet 5.5, and 10% on Haiku 5.5.

Frequently asked questions

What's the difference between Claude Sonnet and Claude Haiku pricing?

Sonnet is Anthropic's mid-tier model, balancing capability and cost, while Haiku is the fastest and cheapest tier, aimed at high-volume, latency-sensitive tasks. Haiku typically costs a fraction of Sonnet per token โ€” check the model comparison table above for current rates.

Does prompt caching change my real cost?

Yes, significantly for workloads that repeat the same system prompt or long context across requests. This calculator doesn't apply caching discounts, so your actual bill will likely be lower if you use that feature.

Are these prices official?

Prices are pulled from OpenRouter's live pricing feed with a 24-hour cache, with a hardcoded fallback if that feed is unavailable. Always confirm current pricing on Anthropic's official pricing page before budgeting for production usage.

When does prompt caching not help?

When requests are infrequent, when prompt prefixes vary between calls (even small edits break the match), or when your system prompt is short enough that the cache write premium outweighs the read savings. Caching rewards stable prefixes and steady traffic.

Does Claude's long context window make it more expensive?

The window itself costs nothing โ€” you pay only for tokens you actually send. The risk is behavioral: a large window invites stuffing in more context than the task needs, and every one of those tokens is billed as input on every request that includes it.

Does the estimate include Haiku 5.5's long-prompt rate?

No. The calculator uses Haiku 5.5's standard rate of $0.10 / $0.50 per million tokens, which applies to prompts up to 100,000 tokens. A request whose prompt goes over 100K is billed at $0.50 / $2.50 for the whole request โ€” five times more โ€” and the threshold counts cached tokens too. If your prompts regularly exceed 100K, multiply the Haiku 5.5 line by five, or compare it with Sonnet 5.5 and Opus 5.5, which charge the same rate across their full 1M window.

How much does batch processing actually save?

Anthropic's Batch API discounts both input and output by 50% for work submitted asynchronously with results returned within 24 hours. It stacks with prompt caching, so a cached, batched workload can land near a tenth of the naive per-call price. The catch is latency โ€” batch is for backfills, bulk classification and offline summarization, not for anything a user is waiting on.

Do Claude's thinking tokens get billed?

Yes. On models with extended thinking enabled, the reasoning tokens the model generates before its visible answer are billed as output tokens, at the output rate. A response that shows 500 tokens of text may have produced several thousand tokens of reasoning behind it. If you enable extended thinking, raise the output figure you enter here well above the length of the visible answer.

Curious where these numbers come from? Read our pricing methodology.