Anthropic’s Claude 4.5 and 4.6 models have aggressively undercut the premium LLM market, bringing flagship intelligence down to commodity prices. At $3.00 per million input tokens for Sonnet 4.5, high-end reasoning is now cheaper than what mid-tier models cost two years ago. For an enterprise processing 10,000 complex support tickets daily (approx. 15M input tokens/month), the bill on Sonnet 4.5 lands around $45—a fraction of the $200+ you’d pay on legacy GPT-4 class models.
This API is defined by two features: reliable steerability and "Computer Use." While OpenAI chases voice modes and video generation, Anthropic has doubled down on text-based reasoning and agentic control. The Computer Use capability—allowing the model to view screens, move cursors, and click buttons—is the moat. It’s not just a chatbot API; it’s a v1 remote worker. It’s imperfect and can struggle with scrolling or drag-and-drop, but for automating legacy software with no API, it’s the only game in town.
Prompt Caching is the other killer feature for developers. If you’re stuffing a 100k-token manual into every request for a RAG bot, caching drops that input cost by 90% (to $0.30/1M on Sonnet) and cuts latency by 85%. It turns the "context window tax" into a rounding error. The 1M token context window on Tier 4 accounts finally makes "chat with your entire repo" a reality without bankrupting your department.
The downsides are predictable for Anthropic: safety filters. The API can be puritanical, occasionally refusing benign requests about "hacking" or medical advice unless you spend time tuning the system prompts. Rate limits on new tiers are also notoriously tight compared to OpenAI’s instant-scale approach. You will hit 429 errors early if you don’t pre-purchase credits to climb tiers.
Skip Claude if you need loose content policies or native real-time audio. Use it if you’re building complex text workflows, coding agents, or need to process massive context at a price that doesn't make your CFO sweat.
Pricing
The pricing hierarchy is now Haiku ($1/$5), Sonnet ($3/$15), and Opus ($5/$25). The free tier is for the chat interface only; the API requires a pre-paid credit deposit ($5 minimum) to start. The real cost cliff is "Extended Thinking"—reasoning tokens are billed as output, meaning a hard problem could burn 10k "thinking" tokens at the expensive output rate ($15-25/1M) before generating a single word of answer. Prompt Caching is the cheat code: cache reads are 90% cheaper than fresh inputs, effectively subsidizing heavy RAG workloads.
Technical Verdict
The Python SDK (anthropic) is stable and typed, though less feature-rich than OpenAI's. Latency on Sonnet 4.5 is excellent (~350ms TTFT), but "Computer Use" loops are slow due to screenshot processing. Documentation is clean but often lags behind beta features like the computer-use-2025 headers. Integration is trivial, but handling the specific tool-use schema for agents requires more boilerplate than competitors.
Quick Start
# pip install anthropic
import anthropic
client = anthropic.Anthropic(api_key="sk-...")
message = client.messages.create(
model="claude-3-5-sonnet-latest",
max_tokens=1000,
messages=[{"role": "user", "content": "Explain quantum computing in one sentence."}]
)
print(message.content[0].text)Watch Out
- Extended Thinking tokens are billed as expensive output tokens, not input.
- Computer Use is beta and struggles with non-standard UI elements like custom scrollbars.
- Rate limits for Tier 1 accounts are very low (often 50 RPM); pre-pay $50+ to upgrade immediately.
- Prompt Caching only saves money if the cache is hit within 5 minutes (TTL resets on read).