Benchmark comparison
Opus 4.8 leads model benchmark leaderboard on performance and cost efficiency
Anthropic Claude Opus 4.8 Max tops an 18-configuration benchmark comparison at 64.8% aggregate performance and $11.02 per task. OpenAI GPT-5.5 Extra High ranks second at 64.3% for $4.37 per task. Cursor Composer 2.5 ranks third at 63.2% for $0.55 per task — the strongest cost-eff
Use-case verdicts
What leaders should use this model for
Coding and engineering
Claude Opus 4.8 Max
Claude Opus 4.8 Max has the strongest current signal for coding and engineering.
medium confidenceWriting and productivity
Claude Opus 4.8 Max
Claude Opus 4.8 Max has the strongest current signal for writing and productivity.
medium confidenceResearch and reasoning
Claude Opus 4.8 Max
No clear public winner yet for research and reasoning.
low confidenceImage, media and documents
Claude Opus 4.8 Max
No clear public winner yet for image, media and documents.
low confidenceCost-sensitive scale
Claude Opus 4.8 Max
Claude Opus 4.8 Max has the strongest current signal for cost-sensitive scale.
medium confidenceEnterprise control and risk
Claude Opus 4.8 Max
No clear public winner yet for enterprise control and risk.
low confidenceModel cards
Where each model fits
Anthropic
Claude Opus 4.8 Max
Coding, advanced math, and long-context tasks where accuracy is the primary constraint
- Not best for: Do not switch production defaults until the model is tested on internal work.Cost: Input not specified and output not specified per million tokens.Governance: Check data handling, model availability, and fallback plans before broad rollout.
OpenAI
GPT-5.5 Extra High
High-accuracy tasks where per-task cost must stay below $5 and a single vendor relationship is preferred
- Not best for: Do not switch production defaults until the model is tested on internal work.Cost: Input not specified and output not specified per million tokens.Governance: Check data handling, model availability, and fallback plans before broad rollout.
Cursor
Composer 2.5
Cost-sensitive coding and development workflows where near-frontier performance is acceptable at a fraction of the price
- Not best for: Do not switch production defaults until the model is tested on internal work.Cost: Input not specified and output not specified per million tokens.Governance: Check data handling, model availability, and fallback plans before broad rollout.
Anthropic
Claude Opus 4.7
Long-horizon agentic tasks and graduate-level reasoning where Opus 4.8's regressions are a concern
- Not best for: Do not switch production defaults until the model is tested on internal work.Cost: Input not specified and output not specified per million tokens.Governance: Check data handling, model availability, and fallback plans before broad rollout.
Anthropic
Claude Sonnet 4.6 Max
Mid-tier tasks where budget is constrained and top-frontier accuracy is not required
- Not best for: Do not switch production defaults until the model is tested on internal work.Cost: Input not specified and output not specified per million tokens.Governance: Check data handling, model availability, and fallback plans before broad rollout.
Anthropic
Claude Sonnet 4.6 Low
High-volume, low-stakes automation where cost minimisation is the primary objective
- Not best for: Do not switch production defaults until the model is tested on internal work.Cost: Input not specified and output not specified per million tokens.Governance: Check data handling, model availability, and fallback plans before broad rollout.
EvidenceRaw benchmark scores and sources
| Use case | Model | Metric | Result | Source |
|---|---|---|---|---|
| Coding and engineering | Claude Opus 4.8 Max | Aggregate performance rank | 1st of 18 (64.8%) | anthropic.com |
| Coding and engineering | Claude Opus 4.8 Max | Cost per task | $11.02 | anthropic.com |
| Coding and engineering | Claude Opus 4.8 Max | SWE-bench Verified | 88.6 | anthropic.com |
| Coding and engineering | Claude Opus 4.8 Max | SWE-bench Pro | 69.2 | anthropic.com |
| Coding and engineering | Claude Opus 4.8 Max | SWE-bench Multilingual | 84.4 | anthropic.com |
| Coding and engineering | Claude Opus 4.8 Max | USAMO 2026 | 96.7 | anthropic.com |
| Coding and engineering | Claude Opus 4.8 Max | GraphWalks long-context | 68.1 | anthropic.com |
| Coding and engineering | Claude Opus 4.8 Max | GPQA Diamond | 93.6 | anthropic.com |
| Cost-sensitive scale | GPT-5.5 Extra High | Aggregate performance rank | 2nd of 18 (64.3%) | anthropic.com |
| Cost-sensitive scale | GPT-5.5 Extra High | Cost per task | $4.37 | anthropic.com |
| Coding and engineering | Composer 2.5 | Aggregate performance rank | 3rd of 18 (63.2%) | anthropic.com |
| Coding and engineering | Composer 2.5 | Cost per task | $0.55 | anthropic.com |
| Coding and engineering | Claude Opus 4.7 | GPQA Diamond | 94.2 | anthropic.com |
| Coding and engineering | Claude Opus 4.7 | USAMO 2026 | 69.3 | anthropic.com |
| Coding and engineering | Claude Opus 4.7 | GraphWalks long-context | 40.3 | anthropic.com |
| Coding and engineering | Claude Opus 4.7 | SWE-bench Verified | 87.6 | anthropic.com |
| Coding and engineering | Claude Opus 4.7 | SWE-bench Pro | 64.3 | anthropic.com |
| Coding and engineering | Claude Opus 4.7 | SWE-bench Multilingual | 80.5 | anthropic.com |
| Coding and engineering | Claude Opus 4.7 | Bio-hard Mythos | 24.7 | anthropic.com |
| Coding and engineering | Claude Opus 4.7 | Vending-Bench 2 max effort | $10.9k output value | anthropic.com |
| Writing and productivity | Claude Sonnet 4.6 Max | Aggregate performance rank | 11th of 18 (49.0%) | anthropic.com |
| Cost-sensitive scale | Claude Sonnet 4.6 Max | Cost per task | $3.09 | anthropic.com |
| Cost-sensitive scale | Claude Sonnet 4.6 Low | Aggregate performance rank | 17th of 18 (41.5%) | anthropic.com |
| Cost-sensitive scale | Claude Sonnet 4.6 Low | Cost per task | $1.89 | anthropic.com |