Claude 4.5 Haiku vs Claude 3.5 Haiku
Compare Claude 4.5 Haiku and Claude 3.5 Haiku. Find out which one is better for your use case.
Model Comparison
| Feature | Claude 4.5 Haiku | Claude 3.5 Haiku |
|---|---|---|
| Provider | Anthropic | Anthropic |
| Model Type | text | text |
| Context Window | 200,000 tokens | 200,000 tokens |
| Input Cost | $1.00 / 1M tokens | $0.80 / 1M tokens |
| Output Cost | $5.00 / 1M tokens | $4.00 / 1M tokens |
Strengths & Best Use Cases
Claude 4.5 Haiku
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 3.5 Haiku
1. Intelligence & Benchmark Performance
- Matches Claude 3 Opus (previous largest model) on many intelligence tasks.
- Surpasses Claude 3 Opus on multiple evaluations despite being a smaller, faster model.
- Major improvements across every skill category vs previous Haiku.
2. Coding Strength
-
Scores 40.6% on SWE-bench Verified, outperforming:
- Claude 3.5 Sonnet (original version)
- GPT-4o
- Many agent-driven systems
-
Excellent for engineering assistants, agent coding tasks, and bug fixing.
3. Speed & Latency
- Same speed class as Claude 3 Haiku (ultra-fast).
- Ideal for real-time interactions, high request volumes, and UI responsiveness.
4. Tool Use & Instruction Following
- Better at following instructions than previous Haiku.
- Stronger at tool use accuracy, making it reliable for agents and workflows.
5. Best Use Cases
- High-volume, low-latency tasks
- User-facing products
- Sub-agent tasks in larger workflows
- Processing large structured datasets (pricing, inventory, purchase history)
- Rapid content or code generation where speed matters
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