Claude Opus 5.5 vs Sonnet 5.5 vs Haiku 5.5: Which One Should You Use?
Anthropic released three Claude 5.5 models in three weeks. The surprise: by Anthropic's own numbers, the mid-priced Sonnet beats Opus on agentic coding. A plain guide to picking one, with prices.
यह लेख हिंदी में पढ़ेंAnthropic released Claude Opus 5.5 on 22 September, Sonnet 5.5 on 28 September and Haiku 5.5 on 7 October. All three are on the Claude API, AWS, Google Cloud and Microsoft Azure. Here is how they compare, using Anthropic's own published figures.
Prices side by side
| Model | Input (per 1M) | Output (per 1M) | Cache reads (per 1M) |
|---|---|---|---|
| Opus 5.5 | $4 | $20 | $0.20 |
| Sonnet 5.5 | $2 | $10 | $0.10 |
| Haiku 5.5 (prompts up to 100K) | $0.10 | $0.50 | $0.01 |
| Haiku 5.5 (prompts over 100K) | $0.50 | $2.50 | $0.05 |
Opus 5.5 also has a fast mode — up to 2.5 times faster — at double the price ($8 / $40). For the previous generation, Haiku 4.5 cost $1 / $5, so Haiku 5.5 is 90% cheaper for prompts up to 100K tokens.
Anthropic's benchmarks
| Benchmark | Opus 5.5 | Sonnet 5.5 | Haiku 5.5 |
|---|---|---|---|
| Terminal-Bench 4.0 (agentic coding) | 66.4% | 70.6% | 39.2% |
| OSWorld 2.1 (computer use) | 81.8% (partial) | 80.1% (partial) | 72.4% (offline subset) |
| CursorBench 4.0 | 57.8% | 55.5% | — |
Two cautions. These are Anthropic's numbers, not independent tests. And the Haiku OSWorld score uses a different subset, so it is not a like-for-like comparison with the other two.
The surprise: Sonnet beats Opus on agentic coding
On Terminal-Bench 4.0, Sonnet 5.5 scores 70.6% against Opus 5.5's 66.4%, at half the price. On computer use and knowledge work it is within a couple of points. Anthropic still positions Opus 5.5 as the stronger model for complex, open-ended work — but for well-defined tasks, the cheaper model is the better buy.
Which one for what
| If you are… | Use |
|---|---|
| Building a coding assistant or production agent | Sonnet 5.5 |
| Doing long, open-ended research or hard multi-step problems | Opus 5.5 |
| Summarising, classifying or extracting at high volume | Haiku 5.5 |
| Running sub-agents under a bigger model | Haiku 5.5 |
| Coding in your terminal with Claude Code | Sonnet 5.5 by default, Opus 5.5 for hard tasks |
Three things that change the bill
- Opus 5.5 always thinks. Thinking mode cannot be switched off, so even short requests pay for some reasoning tokens. That makes it a poor choice for simple, high-volume calls.
- Haiku's 100K line. Above 100,000 tokens in a prompt, Haiku 5.5 costs five times more. Trim context to stay under it.
- Caching. All three charge a fraction of the input price for cached reads. Agents that re-send the same instructions and documents should use prompt caching — it often matters more than the headline rate.
Anthropic bills in US dollars; Indian teams also pay GST and card or bank charges on top. Our AI cost calculator lets you compare monthly costs with your own token counts.
Sources
- Anthropic: Introducing Claude Opus 5.5 (22 September 2026)
- Anthropic: Introducing Claude Sonnet 5.5 (28 September 2026)
- Anthropic: Introducing Claude Haiku 5.5 (7 October 2026)
Frequently asked questions
Which Claude 5.5 model is best for coding?
For most coding work, Sonnet 5.5. Anthropic's own Terminal-Bench 4.0 results put it at 70.6%, ahead of Opus 5.5 at 66.4%, at half the price. Opus 5.5 is recommended for complex, open-ended problems.
How much does Claude Haiku 5.5 cost?
$0.10 per million input tokens and $0.50 per million output tokens for prompts up to 100,000 tokens, and $0.50 and $2.50 above that — 90% cheaper than Haiku 4.5 for shorter prompts.
Is Claude Opus 5.5 better than Claude Fable 5.1?
Anthropic says Opus 5.5 performs at the level of Fable 5.1 on most work and scores higher on Terminal-Bench 4.0 (66.4% vs 55.8%), at $4/$20 per million tokens against Fable 5.1's $10/$50.
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AICreatorHub Team
The AICreatorHub editorial team is a group of hands-on AI practitioners, writers and developers based in India. We test AI tools and models ourselves, track official releases from OpenAI, Anthropic, Google, Meta and xAI, and translate them into simple, India-first guides in English and Hindi. Every article is written for real Indian use cases — pricing in rupees, free-tier tips and practical, tested steps — so you get accurate, up-to-date and genuinely useful AI information.