Anthropic's lineup has turned over again — the current line is Claude Fable 5.1, Claude Opus 5.5, Claude Sonnet 5.5, and Claude Haiku 5.5, with Opus 5, Sonnet 5 and Haiku 4.5 now legacy. After running Claude across a few production contexts, here's where I've landed: the instruction-following is more reliable than the comparable GPT tier for anything that needs structured output, every current model (including Haiku) has a full 1M token context window, and prompt caching discounts of 90–97.5% off cached tokens are still not talked about enough.
The big shifts this generation are at both ends: Opus 5.5 drops to $4/$20 (from Opus 5's $5/$25), Haiku 5.5 falls to $0.10/$0.50 for prompts up to 100K tokens (from Haiku 4.5's $1/$5), and Fable 5.1 adds a new $10/$50 top tier. Sonnet 5.5 holds at $2/$10 — exactly level with OpenAI's GPT-6.1 Sol. Whether Claude ends up cheaper than the GPT tier for your use case depends mostly on how much repeated context you're sending and which tier you actually need. Here's the breakdown.
| Model | Input (per 1M tokens) | Output (per 1M tokens) | Context window |
|---|---|---|---|
| Claude Fable 5.1 | $10.00 | $50.00 | 1M |
| Claude Opus 5.5 | $4.00 | $20.00 | 1M |
| Claude Sonnet 5.5 | $2.00 | $10.00 | 1M |
| Claude Haiku 5.5 | $0.10 | $0.50 | 1M |
| Claude Opus 5 (legacy) | $5.00 | $25.00 | 1M |
| Claude Sonnet 5 (legacy) | $2.00 | $10.00 | 1M |
| Claude Haiku 4.5 (legacy) | $1.00 | $5.00 | 200K |
Source: platform.claude.com/docs pricing, November 2026. Haiku 5.5 is shown at its rate for prompts up to 100K tokens; above that it's $0.50/$2.50. Legacy Claude 5 and 4.x models remain available at their prior pricing (e.g. Opus 5 at $5/$25, Sonnet 4.6 at $3/$15). For the full cross-provider table, see the 2026 AI API pricing guide.
Claude Sonnet 5.5 is the model most teams should default to, priced at $2.00/$10.00 per million tokens — identical to GPT-6.1 Sol on both input and output. Where it consistently shines in practice: complex instruction-following, long-document reasoning, and careful adherence to structured output formats. Teams building on Sonnet tend to need fewer retries and less prompt engineering to get consistent structured outputs.
It includes the full 1M-token context window at standard pricing, so entire contracts, technical manuals, or codebases fit in a single request without chunking — and the price drop from the 4.x generation makes it materially cheaper to run at scale.
Claude Haiku 5.5 at $0.10/$0.50 per million tokens (for prompts up to 100K tokens) is where things get interesting — a 90% price cut from Haiku 4.5, matching GPT-6 Luna on sticker price, with a full 1M context window. Two caveats: prompts over 100K tokens jump to $0.50/$2.50, and Haiku 5.5 uses Anthropic's newer tokenizer, so the same text counts as roughly 30% more tokens than on Haiku 4.5.
If your workload needs better instruction-following or structured-output quality than a bottom-tier model delivers, but you can't justify full Sonnet pricing, Haiku 5.5 is worth evaluating seriously — Anthropic positions it for high-volume classification, extraction, routing and subagent work.
Opus used to be a luxury — Claude 3 Opus launched at $15/$75 per million tokens. Opus 5.5 lands at $4/$20 — below the $5/$25 Opus 4.5–5 price point — which makes top-tier reasoning even more practical for long-running agentic coding and knowledge work. Above it, Claude Fable 5.1 ($10/$50) is the new tier for the most demanding reasoning and long-horizon agentic work. For the other 90% of production work, start with Sonnet 5.5 and only escalate when quality demands it.
This is Anthropic's biggest competitive pricing advantage and it's often overlooked. On the current models a cache hit costs 2.5–10% of the standard input rate — $0.10/M on Sonnet 5.5 (5%), $0.20/M on Opus 5.5 (5%), and $0.25/M on Fable 5.1 (2.5%). (OpenAI's GPT-6 line now prices cache reads at a similar 5–10%, so the gap has narrowed.)
For applications with large, consistent system prompts or document contexts that repeat across requests, this is a massive lever. A 3,000-token system prompt on Sonnet 5.5 costs $0.10 per million tokens on cache hits vs $2.00 uncached.
Imagine you're building a RAG system that sends a 4,000-token document context plus a 500-token system prompt with each request. At 30,000 requests/month on Claude Sonnet 5.5 ($2/$10):
| Scenario | Input cost | Output cost (300 tokens avg) | Monthly total |
|---|---|---|---|
| No caching | $270.00 | $90.00 | $360.00 |
| With caching (system prompt + doc) | $13.50 | $90.00 | $103.50 |
That's roughly a 71% reduction just from caching (before the one-time cache-write cost), with no quality change. This is one of the most impactful optimizations available for high-volume Claude applications.
At the workhorse tier it's now a dead heat — Sonnet 5.5 and GPT-6.1 Sol are both $2/$10, with the same $0.10/M cache-hit rate — so the choice comes down to quality on your workload. At the top end, Opus 5.5 ($4/$20) is well below GPT-6 Astra ($10/$50). Claude tends to come out ahead on:
For workloads with minimal repeated context and very short prompts, Haiku 5.5 and GPT-6 Luna are tied at $0.10/$0.50 and both undercut Gemini's Flash tiers. For most production coding and analysis workloads, Sonnet 5.5 is both strong and price-competitive.
Compare Claude 5.5 vs GPT-6 vs Gemini 4 for your exact token volumes and request rate.
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