Claude 3 Family: Haiku, Sonnet and Opus Compared

Anthropic launched the Claude 3 family on March 4, 2024: three models (Haiku, Sonnet, and Opus) on the same date, each with a different cost/performance trade-off. A month in, adoption was clear: Claude 3 Opus competes head-to-head with GPT-4 Turbo on the published benchmarks, and Haiku is one of the cheapest models with decent quality. See also: Claude 2: Anthropic’s Alternative to GPT-4.

Key takeaways

• The three tiers cover clear trade-offs: Haiku for cheap high volume, Sonnet as pragmatic default, Opus for complex reasoning where a cheaper model’s error is expensive.

• All three have 200k token context, a concrete advantage over GPT-4 Turbo’s 128k.

• Multimodal vision (images in prompts) is available across all three models.

• Tiered routing (Haiku → Sonnet → Opus as needed) minimises total cost without sacrificing quality where it matters.

• Available on Amazon Bedrock and Google Cloud Vertex AI, opening European compliance options.

The three tiers

Haiku: fastest and cheapest:

• Price: $0.25 / 1M input tokens, $1.25 / 1M output.

• Context: 200k tokens.

• Ideal use: classification, simple extraction, tier-1 support chat, content moderation.

Sonnet: balanced:

• Price: $3 / 1M input, $15 / 1M output.

• Context: 200k tokens.

• Quality: near GPT-4 on many tasks.

• Ideal use: enterprise RAG, agents with tools, long-document analysis.

Opus, most capable:

• Price: $15 / 1M input, $75 / 1M output.

• Context: 200k tokens.

• Quality: competitive with GPT-4 Turbo.

• Ideal use: complex multi-step reasoning, research, advanced coding, legal/medical analysis.

Published benchmarks

Opus is in GPT-4 Turbo’s class. Sonnet closes at roughly GPT-3.5+ quality at a lower price. Haiku is the surprise: competitive for its price, 12x cheaper than Sonnet.

The 200k context: the real differentiator

Both Anthropic (Claude 3) and Google (Gemini 1.5 Pro with 1M) make long context accessible. OpenAI stays at 128k for GPT-4 Turbo.

Cases where 200k suffices without needing Gemini 1.5:

• Books of ~150 pages or ~75k words.

• Mid-size codebases.

• Hour-long audio transcripts.

• Extensive technical reports.

For millions of tokens, Gemini 1.5 Pro still leads. For hundreds of thousands, Claude 3 is competitive.

Multimodal vision: images in prompts

All three models accept images in prompts. Claude 3 Opus is particularly strong at:

• Document OCR.

• Chart and diagram description.

• Technical schematic analysis.

• Data extraction from invoices and forms.

There is no image generation (that is DALL-E, Midjourney, or Stable Diffusion territory).

Vs GPT-4 Turbo: practical differences

After months of parallel use:

• Factual accuracy: Opus and GPT-4 Turbo are roughly tied.

• Instruction following: Claude 3 tends to be better on complex instructions.

• Reasoning: excellent in both; hard to separate consistently.

• Coding: similar.

• Refusal rate: Claude has historically been more cautious; Claude 3 is less rigid.

• Tone: Claude tends to be more verbose by default.

No universal winner. Evaluate with your own use cases. Claude 3 and GPT-4 are complementary, not mutually exclusive.

Running both in a multi-provider strategy makes sense, especially for European compliance where data residency matters. This connects directly with LiteLLM and LLM proxies for abstracting provider choice.

Multi-tier usage strategy

The most efficient pattern:

• Classify intent with Haiku (cheap, ~$0.25/1M tokens).

• Process simple case with Sonnet (default).

• Escalate to Opus only if Sonnet fails or requires high precision.

This tiered routing with LiteLLM or custom logic minimises total cost without sacrificing quality where it matters.

API and access

• Anthropic API direct.

• Amazon Bedrock, with regional options that ease European compliance.

• Google Cloud Vertex AI, integrating with the GCP ecosystem.

• Azure: no (OpenAI exclusive on Azure).

Honest limitations

• Aggressive rate limits at start of Pro plan.

• Data residency: US by default (Bedrock has regional options).

• No fine-tuning: Anthropic does not offer custom fine-tune except via enterprise contracts.

Conclusion

The Claude 3 family closes the gap Anthropic had vs OpenAI in top-tier capability. Opus is a real option for frontier tasks. Sonnet is the pragmatic default. Haiku opens high-volume cases with decent quality.

200k context across all three is a concrete advantage vs GPT-4 Turbo. The Anthropic-vs-OpenAI choice is no longer "who has the best" but "which fits your case and provider preference". Worth having both in your strategy, not just one.

Frequently asked questions

How much do Claude 3 Haiku, Sonnet and Opus cost per million tokens?

Haiku costs $0.25 per million input tokens and $1.25 per million output; Sonnet, $3 input and $15 output; Opus, $15 input and $75 output. All three share a 200k token context window and accept images in prompts. Haiku is the surprise of the family: competitive for its price and 12x cheaper than Sonnet, which makes it suited to classification, simple extraction, tier-1 support chat and content moderation.

Is Claude 3 Opus really on par with GPT-4 Turbo?

On the published benchmarks, yes: Opus scores 86.8 on MMLU against GPT-4 Turbo's 86.4, and 95.0 against 92.0 on GSM8K. On HumanEval it is 84.9 against 85.4, and on HellaSwag 95.4 against 95.3. In months of parallel use, factual accuracy is roughly tied, Claude 3 tends to follow complex instructions better, coding is similar and Claude is more verbose by default. There is no universal winner, so evaluate with your own use cases.

Can I use Claude 3 from a cloud provider for European compliance?

Yes. Besides the direct Anthropic API, the Claude 3 models are available on Amazon Bedrock, whose regional options ease European compliance, and on Google Cloud Vertex AI. They are not on Azure, which is OpenAI-exclusive. Data residency is US by default, rate limits were aggressive at the start of the Pro plan, and Anthropic offers no custom fine-tuning except via enterprise contracts.