Compare · ModelsLive · 3 picked · head to head
Claude Fable 5 vs Claude Opus 4.8 vs GPT-5.4
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Claude Fable 5 wins on 11/19 benchmarks
Claude Fable 5 wins 11 of 19 shared benchmarks. Leads in agentic · arena · math.
Category leads
agentic·Claude Fable 5arena·Claude Fable 5knowledge·GPT-5.4math·Claude Fable 5coding·Claude Fable 5speed·Claude Fable 5reasoning·GPT-5.4
Hype vs Reality
Attention vs performance
Claude Fable 5
#12 by perf·no signal
Claude Opus 4.8
#47 by perf·no signal
GPT-5.4
#61 by perf·no signal
Best value
GPT-5.4
1.6x better value than Claude Opus 4.8
Claude Fable 5
2.5 pts/$
$30.00/M
Claude Opus 4.8
4.1 pts/$
$15.00/M
GPT-5.4
6.7 pts/$
$8.75/M
Vendor risk
Who is behind the model
Anthropic
$380.0B·Tier 1
Anthropic
$380.0B·Tier 1
OpenAI
$840.0B·Tier 1
Head to head
19 benchmarks · 3 models
Claude Fable 5Claude Opus 4.8GPT-5.4
APEX-Agents
Claude Fable 5 leads by +2.5
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
Claude Fable 5
45.0
Claude Opus 4.8
42.5
GPT-5.4
35.9
Chatbot Arena Elo · Coding
Claude Fable 5 leads by +111.7
Claude Fable 5
1653.9
Claude Opus 4.8
1542.3
GPT-5.4
1411.1
Chatbot Arena Elo · Overall
Claude Fable 5 leads by +29.7
Claude Fable 5
1507.6
Claude Opus 4.8
1477.8
GPT-5.4
1467.7
Chess Puzzles
GPT-5.4 leads by +3.0
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
Claude Fable 5
41.0
Claude Opus 4.8
34.0
GPT-5.4
44.0
FrontierMath-Tier-4-v2-Private
Claude Fable 5 leads by +31.7
Claude Fable 5
87.8
Claude Opus 4.8
56.1
GPT-5.4
49.0
FrontierMath-Tiers-1-3-v2-Private
Claude Fable 5 leads by +7.0
Claude Fable 5
87.0
Claude Opus 4.8
80.0
GPT-5.4
78.6
OTIS Mock AIME 2024-2025
Claude Fable 5 leads by +1.4
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Claude Fable 5
99.7
Claude Opus 4.8
98.3
GPT-5.4
95.3
SimpleQA Verified
Claude Fable 5 leads by +23.5
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
Claude Fable 5
68.3
Claude Opus 4.8
39.5
GPT-5.4
44.8
WeirdML
Claude Fable 5 leads by +5.0
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
Claude Fable 5
87.8
Claude Opus 4.8
82.9
GPT-5.4
77.7
Artificial Analysis · Agentic Index
GPT-5.4 leads by +16.6
Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?"
Claude Fable 5
52.8
GPT-5.4
69.4
Artificial Analysis · Coding Index
Claude Fable 5 leads by +19.2
Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads.
Claude Fable 5
76.5
GPT-5.4
57.3
Artificial Analysis · Quality Index
Claude Fable 5 leads by +2.7
Claude Fable 5
59.9
GPT-5.4
57.2
ARC-AGI
GPT-5.4 leads by +1.2
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
GPT-5.4
93.7
ARC-AGI-2
GPT-5.4 leads by +1.9
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
GPT-5.4
74.0
FrontierMath-2025-02-28-Private
GPT-5.4 leads by +0.4
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
GPT-5.4
47.6
FrontierMath-Tier-4-2025-07-01-Private
Claude Opus 4.8 leads by +4.1
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
GPT-5.4
27.1
GPQA diamond
GPT-5.4 leads by +3.0
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
GPT-5.4
91.1
PostTrainBench
Claude Opus 4.8 leads by +17.0
Claude Opus 4.8
37.2
GPT-5.4
20.2
SimpleBench
Claude Fable 5 leads by +20.5
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
Claude Fable 5
78.3
Claude Opus 4.8
57.8
Full benchmark table
| Benchmark | Claude Fable 5 | Claude Opus 4.8 | GPT-5.4 |
|---|---|---|---|
APEX-Agents APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments. | 45.0 | 42.5 | 35.9 |
Chatbot Arena Elo · Coding | 1653.9 | 1542.3 | 1411.1 |
Chatbot Arena Elo · Overall | 1507.6 | 1477.8 | 1467.7 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | 41.0 | 34.0 | 44.0 |
FrontierMath-Tier-4-v2-Private | 87.8 | 56.1 | 49.0 |
FrontierMath-Tiers-1-3-v2-Private | 87.0 | 80.0 | 78.6 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 99.7 | 98.3 | 95.3 |
SimpleQA Verified SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information. | 68.3 | 39.5 | 44.8 |
WeirdML WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns. | 87.8 | 82.9 | 77.7 |
Artificial Analysis · Agentic Index Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?" | 52.8 | — | 69.4 |
Artificial Analysis · Coding Index Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads. | 76.5 | — | 57.3 |
Artificial Analysis · Quality Index | 59.9 | — | 57.2 |
ARC-AGI ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization. | — | 92.5 | 93.7 |
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 | 74.0 |
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 | 47.6 |
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 | 27.1 |
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 | 91.1 |
PostTrainBench | — | 37.2 | 20.2 |
SimpleBench SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking. | 78.3 | 57.8 | — |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $10.00 | $50.00 | 1.0M tokens (~500 books) | $200.00 | |
| $5.00 | $25.00 | 1.0M tokens (~500 books) | $100.00 | |
| $2.50 | $15.00 | 1.1M tokens (~525 books) | $56.25 |