haiku-vs-sonnet-performance

Executive Summary

Speed: Haiku 4.5 is 3-5x faster than Sonnet 4.5 Latency: Sub-200ms response time for small prompts Cost: 1/3 the price of Sonnet 4.5 (5 vs 15 per million tokens) Quality Trade-off: Achieves 90% of Sonnet’s performance while being dramatically faster

Speed & Latency Metrics

Official Performance Claims

From Anthropic’s announcement:

4-5x faster than Sonnet 4.5
More than 2x faster than Sonnet 4.0
Sub-200ms response time for small prompts
3x faster in comparable workloads (third-party benchmarks)

Context: Previous Generation (Claude 3.5 Haiku)

While Anthropic hasn’t published specific TTFT/tokens-per-second for Haiku 4.5, third-party testing of Claude 3.5 Haiku showed:

Time to First Token (TTFT): 0.36 seconds
Throughput: 52.54 tokens/second

These metrics likely improved further in the 4.5 generation.

Performance vs Quality Trade-off

Coding Performance

SWE-bench Verified Scores:

Haiku 4.5: 73.3%
Sonnet 4.5: 77.2%
Gap: Only 3.9 percentage points

Augment Agentic Coding Evaluation:

Haiku 4.5 achieves 90% of Sonnet 4.5’s performance
Delivers “similar coding performance to Sonnet 4 at one-third the cost and more than twice the speed”

Quality Characteristics

Where Sonnet Excels:

Complex reasoning tasks
Mathematical problem-solving
Deep code understanding
Nuanced contextual analysis

Where Haiku Excels:

Speed-critical applications
High-throughput pipelines
Real-time interactions
Cost-sensitive deployments

Cost Analysis

Model	Input (per 1M tokens)	Output (per 1M tokens)	Relative Cost
Haiku 4.5	$1	$5	1x (baseline)
Sonnet 4.5	$3	$15	3x

Implications:

Same budget = 3x more Haiku requests
Same throughput = 1/3 the cost with Haiku
For high-volume applications, cost savings can be substantial

When the Speed Difference Matters

Critical Use Cases

Conversational Interfaces
- Chat UIs where milliseconds affect perceived responsiveness
- Live assistance tools requiring instant feedback
- Customer service agents handling multiple conversations
Programmatic Pipelines
- Batch processing where milliseconds aggregate
- CI/CD workflows processing many files
- Automated testing and code review
Real-Time Applications
- Pair programming with inline suggestions
- Live code completion
- Interactive debugging assistance
High-Volume Operations
- Processing hundreds/thousands of requests
- Multi-agent systems with parallel execution
- Bulk document analysis

When Speed Matters Less

Complex architectural decisions (use Sonnet)
Deep code analysis requiring nuanced understanding (use Sonnet)
Single-request workflows where absolute quality > speed (use Sonnet)
Budget-unlimited, quality-critical applications (use Sonnet)

Real-World Performance Impact

User Experience

Sub-200ms latency means:

Users perceive responses as “instant”
No perceived lag in conversational flow
Maintains engagement in interactive sessions
Enables real-time pair programming feel

3-5x speedup translates to:

Sonnet: 5 seconds → Haiku: 1-1.7 seconds
Sonnet: 10 seconds → Haiku: 2-3.3 seconds
Sonnet: 30 seconds → Haiku: 6-10 seconds

Economic Impact

For Claude Code slash commands:

Processing 100 research READMEs:
- Sonnet: Higher quality, 30-50 minutes, higher cost
- Haiku: 90% quality, 6-10 minutes, 1/3 cost
- 10-20x total efficiency gain (speed + cost)

Benchmark Summary

Metric	Haiku 4.5	Sonnet 4.5	Winner
Speed	3-5x faster	Baseline	Haiku
Latency	Sub-200ms	~600-1000ms	Haiku
Cost	5	15	Haiku
SWE-bench	73.3%	77.2%	Sonnet
Reasoning	Good	Excellent	Sonnet
Code Quality	90% of Sonnet	100%	Sonnet
Throughput	High	Medium	Haiku

Decision Framework

Use Haiku 4.5 When:

✅ Speed is critical (chat, live tools, real-time) ✅ Volume is high (batch processing, pipelines) ✅ Cost matters (budget-sensitive, high-throughput) ✅ Task is straightforward (templates, formatting, structure) ✅ 90% quality is acceptable ✅ Sub-200ms latency is required

Use Sonnet 4.5 When:

✅ Quality is paramount (complex reasoning, architecture) ✅ Task requires deep understanding ✅ Budget is flexible ✅ Single-request or low-volume ✅ Mathematical/logical precision needed ✅ Nuanced contextual analysis required

Practical Recommendations

For Claude Code Slash Commands

Template-based operations (Haiku):

/new-research - Create standard structure
/research-readme - Generate documentation following template
/research-index - Regenerate index from existing content
/add-frontmatter - Add standard YAML metadata
/research-toc - Generate table of contents

Analysis-based operations (Sonnet):

Complex code reviews requiring deep understanding
Architectural decision documentation
Novel problem-solving without clear templates
Critical bug analysis

For Multi-Agent Systems

Orchestrator: Sonnet (needs to reason about task distribution) Workers: Haiku (executing well-defined sub-tasks)

Result: Best of both worlds - intelligent coordination with fast execution

Observed Performance Patterns

Batch Operations

10 Task subagents with Haiku:

All run in parallel
Complete in ~2-3 minutes total
Cost: 1/3 of Sonnet equivalent
Quality: 90% (acceptable for template tasks)

Same with Sonnet:

Sequential execution required for cost control
~20-30 minutes total
Cost: 3x higher
Quality: 100% (but often unnecessary for templates)

Future Considerations

When to Re-evaluate

New model releases (Haiku 5, Sonnet 5)
Pricing changes
Performance improvements
Task complexity increases
Quality requirements change

Monitoring

Track these metrics in your workflows:

Response time - Is sub-200ms maintained?
Quality - Is 90% sufficient or do you need 100%?
Cost - Are you optimizing spend effectively?
User satisfaction - Does speed improve UX?

Conclusion

Haiku 4.5 provides massive speed and cost advantages (3-5x faster, 1/3 cost) while maintaining 90% of Sonnet’s quality. For template-based, high-volume, or speed-critical tasks, Haiku is the clear winner. Reserve Sonnet for complex reasoning where the extra 10% quality justifies 3x cost and 3-5x slower execution.

The 90/10 rule: If a task can be done with 90% of Sonnet’s quality, use Haiku. Only use Sonnet when you absolutely need that final 10%.