Compare · ModelsLive · 2 picked · head to head
Claude Opus 4.8 vs Claude Opus 4.7
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Claude Opus 4.8 wins on 11/16 benchmarks
Claude Opus 4.8 wins 11 of 16 shared benchmarks. Leads in agentic · knowledge · math.
Category leads
agentic·Claude Opus 4.8reasoning·Claude Opus 4.7arena·Claude Opus 4.7knowledge·Claude Opus 4.8math·Claude Opus 4.8coding·Claude Opus 4.8
Hype vs Reality
Attention vs performance
Claude Opus 4.8
#47 by perf·no signal
Claude Opus 4.7
#65 by perf·no signal
Best value
Claude Opus 4.8
1.1x better value than Claude Opus 4.7
Claude Opus 4.8
4.1 pts/$
$15.00/M
Claude Opus 4.7
3.9 pts/$
$15.00/M
Vendor risk
Who is behind the model
Anthropic
$380.0B·Tier 1
Anthropic
$380.0B·Tier 1
Head to head
16 benchmarks · 2 models
Claude Opus 4.8Claude Opus 4.7
APEX-Agents
Claude Opus 4.8 leads by +8.6
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
Claude Opus 4.8
42.5
Claude Opus 4.7
33.9
ARC-AGI
Claude Opus 4.7 leads by +1.0
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
Claude Opus 4.8
92.5
Claude Opus 4.7
93.5
ARC-AGI-2
Claude Opus 4.7 leads by +3.7
ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data.
Claude Opus 4.8
72.1
Claude Opus 4.7
75.8
Chatbot Arena Elo · Coding
Claude Opus 4.7 leads by +14.6
Claude Opus 4.8
1542.3
Claude Opus 4.7
1556.9
Chatbot Arena Elo · Overall
Claude Opus 4.7 leads by +15.3
Claude Opus 4.8
1477.8
Claude Opus 4.7
1493.1
Chess Puzzles
Claude Opus 4.8 leads by +4.0
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
Claude Opus 4.8
34.0
Claude Opus 4.7
30.0
FrontierMath-2025-02-28-Private
Claude Opus 4.8 leads by +3.5
FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning.
Claude Opus 4.8
47.2
Claude Opus 4.7
43.8
FrontierMath-Tier-4-2025-07-01-Private
Claude Opus 4.8 leads by +8.3
FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning.
Claude Opus 4.8
31.3
Claude Opus 4.7
22.9
FrontierMath-Tier-4-v2-Private
Claude Opus 4.8 leads by +24.4
Claude Opus 4.8
56.1
Claude Opus 4.7
31.7
FrontierMath-Tiers-1-3-v2-Private
Claude Opus 4.8 leads by +9.8
Claude Opus 4.8
80.0
Claude Opus 4.7
70.2
GPQA diamond
Claude Opus 4.8 leads by +1.2
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
Claude Opus 4.8
88.0
Claude Opus 4.7
86.9
OTIS Mock AIME 2024-2025
Claude Opus 4.8 leads by +0.5
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Claude Opus 4.8
98.3
Claude Opus 4.7
97.8
PostTrainBench
Claude Opus 4.8 leads by +8.7
Claude Opus 4.8
37.2
Claude Opus 4.7
28.6
SimpleBench
Claude Opus 4.8 leads by +2.3
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
Claude Opus 4.8
57.8
Claude Opus 4.7
55.5
SimpleQA Verified
Claude Opus 4.7 leads by +11.1
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
Claude Opus 4.8
39.5
Claude Opus 4.7
50.6
WeirdML
Claude Opus 4.8 leads by +6.5
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
Claude Opus 4.8
82.9
Claude Opus 4.7
76.4
Full benchmark table
| Benchmark | Claude Opus 4.8 | Claude Opus 4.7 |
|---|---|---|
APEX-Agents APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments. | 42.5 | 33.9 |
ARC-AGI ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization. | 92.5 | 93.5 |
ARC-AGI-2 ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data. | 72.1 | 75.8 |
Chatbot Arena Elo · Coding | 1542.3 | 1556.9 |
Chatbot Arena Elo · Overall | 1477.8 | 1493.1 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | 34.0 | 30.0 |
FrontierMath-2025-02-28-Private FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning. | 47.2 | 43.8 |
FrontierMath-Tier-4-2025-07-01-Private FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning. | 31.3 | 22.9 |
FrontierMath-Tier-4-v2-Private | 56.1 | 31.7 |
FrontierMath-Tiers-1-3-v2-Private | 80.0 | 70.2 |
GPQA diamond Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs. | 88.0 | 86.9 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 98.3 | 97.8 |
PostTrainBench | 37.2 | 28.6 |
SimpleBench SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking. | 57.8 | 55.5 |
SimpleQA Verified SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information. | 39.5 | 50.6 |
WeirdML WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns. | 82.9 | 76.4 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $5.00 | $25.00 | 1.0M tokens (~500 books) | $100.00 | |
| $5.00 | $25.00 | 1.0M tokens (~500 books) | $100.00 |