speed-analysis

Speed Metrics Overview

Sonnet 4.5 (Confirmed Metrics)

Opus 4.5 (Initial Data - Released Nov 24, 2025)

Note: Opus 4.5 was released today (Nov 24, 2025). Independent speed benchmarks from sites like Artificial Analysis typically take 1-2 weeks to publish comprehensive metrics.

Opus 4.1 (Previous Version - For Reference)

Speed Comparison Matrix

Verdict: Sonnet 4.5 is ~40% faster in raw output speed and ~33% faster to first token.

Total Response Time Analysis

Speed isn’t just about tokens/second - it’s about total time to complete response.

Scenario 1: Short Response (500 tokens)

Sonnet 4.5:

• TTFT: 1.80s
• Generation: 500 / 63 tok/s = 7.9s
• Total: 9.7 seconds

Opus 4.5 (estimated):

• TTFT: 2.5s
• Generation: 500 / 45 tok/s = 11.1s
• Total: 13.6 seconds

Winner: Sonnet (40% faster - 9.7s vs 13.6s)

Scenario 2: Medium Response (2000 tokens)

Sonnet 4.5:

• TTFT: 1.80s
• Generation: 2000 / 63 tok/s = 31.7s
• Total: 33.5 seconds

Opus 4.5 (estimated):

• TTFT: 2.5s
• Generation: 2000 / 45 tok/s = 44.4s
• Total: 46.9 seconds

Winner: Sonnet (40% faster - 33.5s vs 46.9s)

Scenario 3: Token Efficiency Advantage (Opus generates fewer tokens)

Sonnet 4.5 (generates 4000 tokens for equivalent quality):

• TTFT: 1.80s
• Generation: 4000 / 63 tok/s = 63.5s
• Total: 65.3 seconds

Opus 4.5 (generates 1000 tokens - 76% fewer):

• TTFT: 2.5s
• Generation: 1000 / 45 tok/s = 22.2s
• Total: 24.7 seconds

Winner: Opus (62% faster - 24.7s vs 65.3s) when token efficiency matters

When Speed Differences Matter

High-Impact Speed Scenarios

1. Interactive Chat Applications

• User expectation: <2 second response start
• Sonnet 4.5 TTFT: 1.80s ✅
• Opus 4.5 TTFT: ~2.5s ⚠️
• Recommendation: Sonnet for real-time chat

2. High-Frequency API Calls

• 1000 requests/day
• Latency difference: 0.7s per request (TTFT)
• Daily time savings: 1000 × 0.7s = 700 seconds = 11.7 minutes
• Recommendation: Sonnet for batch operations

3. Streaming UI (typewriter effect)

• User perceives speed through TTFT + initial tokens
• First 100 tokens:
  • Sonnet: 1.80s + (100/63) = 3.4s
  • Opus: 2.5s + (100/45) = 4.7s
• Recommendation: Sonnet for better UX

Low-Impact Speed Scenarios

1. Batch Processing (async)

• Total wall time: minutes to hours
• 1-2 second latency difference negligible
• Recommendation: Use quality/cost as decision factors

2. Long-Form Generation

• Generating 10,000+ tokens
• TTFT becomes small percentage of total time
• Token efficiency may compensate for slower tok/s
• Recommendation: Consider token efficiency trade-off

3. Agent Workflows (extended tasks)

• Multi-step reasoning over 30+ minutes
• Individual request latency < 1% of total time
• Quality and reliability more important
• Recommendation: Opus for quality, Sonnet for speed not critical

Latency Optimization Strategies

Strategy 1: Hybrid Routing by Latency Requirement

Request Classification:
├── Interactive (<3s requirement) → Sonnet 4.5
├── Near real-time (3-10s acceptable) → Sonnet or Opus
└── Async/batch (>10s acceptable) → Opus 4.5 (for quality)

Strategy 2: Streaming for Perceived Speed

Both models support streaming. For user-facing applications:

• Stream responses to show progress immediately
• TTFT becomes perceived latency
• Sonnet’s 1.80s TTFT provides better initial experience

Strategy 3: Parallel Execution

For complex tasks requiring multiple LLM calls:

• Use Sonnet for parallel execution (faster individual calls)
• Example: 5 parallel Sonnet calls = ~10s (1.8s TTFT + short generation)
• vs 5 sequential Opus calls = ~70s (slower × 5)

Strategy 4: Token Efficiency as Speed Optimization

When Opus generates 76% fewer tokens:

• Lower token count = faster generation phase
• May offset slower tok/s rate
• Critical for constrained environments (mobile, edge)

Speed × Cost × Quality Trade-offs

Interactive Use Case

Priority: Speed > Cost > Quality
Recommendation: Sonnet 4.5
- TTFT: 1.80s (best UX)
- Cost: $3/$15 (affordable for high volume)
- Quality: 77.2% SWE-bench (sufficient for most)

Batch Processing

Priority: Cost > Quality > Speed
Recommendation: Sonnet 4.5 (or Haiku for simple tasks)
- Speed: 63 tok/s (fast enough for async)
- Cost: $3/$15 (67% cheaper than Opus)
- Quality: 77.2% (good for non-critical)

Complex Reasoning

Priority: Quality > Speed > Cost
Recommendation: Opus 4.5
- Quality: 80.9% SWE-bench (best)
- Speed: ~45 tok/s (acceptable for quality gain)
- Cost: $5/$25 (justified by quality)

Mission-Critical

Priority: Quality > Speed > Cost
Recommendation: Opus 4.5
- Quality: 80.9% (minimize failures)
- Speed: Token efficiency (-76%) may compensate
- Cost: Secondary to correctness

Speed Regression Risk

Risk: If Opus 4.5 is significantly slower than expected

Mitigation:

1. Measure actual latency in production (not estimates)
2. A/B test Sonnet vs Opus on speed-sensitive paths
3. Implement timeout/fallback to Sonnet
4. Monitor p95/p99 latencies (not just median)

Monitoring Metrics:

• TTFT (time to first token)
• Total response time
• Tokens per second
• User-perceived latency (streaming)

Benchmark Availability Timeline

Expected benchmarks for Opus 4.5:

• Independent sites (Artificial Analysis, etc.): 1-2 weeks
• Community benchmarks: Immediate (coming days)
• Production metrics: Available as users deploy

Check these sources:

• Artificial Analysis - Claude Opus 4.5 (not yet published)
• Anthropic’s official docs (may add speed specs)
• Community benchmarks on Twitter/Reddit

Recommendations by Use Case

Speed Outlook

Current state (Nov 24, 2025):

• Sonnet 4.5 is the clear speed leader
• Opus 4.5 likely 20-40% slower in raw tok/s
• Token efficiency may close the gap in some scenarios

Future expectations:

• Opus optimizations may improve speed over time
• Infrastructure improvements benefit both models
• Speed gap likely to remain (flagship vs balanced positioning)

Summary: Sonnet 4.5 is faster (~63 vs ~45 tokens/sec, 1.80s vs ~2.5s TTFT), making it the better choice for latency-sensitive applications like interactive chat, real-time features, and user-facing APIs. However, Opus 4.5’s 76% token efficiency can make it faster in total response time when generating verbose outputs, and for async/batch processing, the speed difference is negligible compared to quality gains.

Key Insight: For most interactive use cases, Sonnet 4.5 wins on speed. For complex reasoning tasks where latency isn’t critical, Opus 4.5’s quality justifies the slower inference.

Sources

• Artificial Analysis - Claude 4.5 Sonnet Speed Metrics
• Artificial Analysis - Claude 4.1 Opus Benchmarks
• Anthropic - Introducing Claude Opus 4.5
• Anthropic - Introducing Claude Sonnet 4.5

Status: Initial analysis based on Sonnet 4.5 confirmed metrics and Opus 4.1 reference data. Will update when independent Opus 4.5 speed benchmarks are published (expected within 1-2 weeks).