LLM ComparisonClaude 4.5 HaikuClaude 4.6 Opus

Claude 4.5 Haiku vs Claude 4.6 Opus

Compare Claude 4.5 Haiku and Claude 4.6 Opus. Build AI products powered by either model on Appaca.

Model Comparison

FeatureClaude 4.5 HaikuClaude 4.6 Opus
ProviderAnthropicAnthropic
Model Typetexttext
Context Window200,000 tokens1,000,000 tokens
Input Cost
$1.00/ 1M tokens
$5.00/ 1M tokens
Output Cost
$5.00/ 1M tokens
$25.00/ 1M tokens

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Strengths & Best Use Cases

Claude 4.5 Haiku

Anthropic

1. Frontier-level coding at small-model speed

  • Similar coding performance to Claude Sonnet 4 at one-third the cost.
  • Runs 4-5x faster than Sonnet 4.5 for many tasks.
  • Ideal for real-time pair programming, prototyping, and rapid iteration.

2. Excellent computer-use abilities

  • Surpasses Claude Sonnet 4 in certain computer-control tasks.
  • Great for agents requiring low-latency tool use (Chrome automation, coding agents, etc.).

3. Perfect for real-time, low-latency applications

  • Chat assistants
  • Customer support agents
  • Interactive development loops
  • Multi-agent orchestration

4. Works seamlessly with Sonnet 4.5 in hybrid agent setups

  • Sonnet 4.5 plans complex workflows.
  • Haiku 4.5 executes subtasks in parallel for speed and cost-efficiency.

5. High alignment & safest Claude model by metric

  • Lower misaligned behavior rates than Haiku 3.5, Sonnet 4.5, and Opus 4.1.
  • Limited CBRN risk → released under AI Safety Level 2 (ASL-2).

Claude 4.6 Opus

Anthropic

1. Anthropic's top model for coding and agents

  • Anthropic positions Opus 4.6 as its most intelligent model for building agents and coding.
  • It builds on Opus 4.5 with higher reliability and precision for professional software engineering, complex agentic workflows, and high-stakes enterprise tasks.

2. Strong frontier performance on real agent benchmarks

  • Anthropic reports state-of-the-art results across coding and agentic evaluations.
  • Public benchmark highlights include 65.4% on Terminal-Bench 2.0, 72.7% on OSWorld, and 90.2% on BigLaw Bench.

3. Best fit for long-horizon, high-context work

  • Supports up to a 1M token context window in beta and up to 128K output tokens.
  • Designed for long-running tasks that need sustained planning, careful debugging, code review, and strong context retention.

4. Advanced reasoning controls and workflow support

  • Supports adaptive thinking and the effort parameter, including the new max effort level.
  • Anthropic also introduced fast mode, compaction, and dynamic filtering with web search and web fetch for Opus 4.6-era agent workflows.

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