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Best For/Best AI for Reasoning
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Best AI for Reasoning

Claude Fable 5 leads HLE (Humanity's Last Exam) in 2026 at 53.3%. Claude Opus 5 Max leads Intelligence Index at 60.7 (Xhigh 60.1, Fable 5 59.9). GPT-5.6 Sol max (HLE 47.2%, GPQA 94.1% co-leader), Claude Opus 4.8 (HLE 45.7%) compared. Ranked by GPQA Diamond, AIME, MATH-500, HLE. Free.

Complex reasoning abilityMathematical problem solvingScientific knowledge depthMulti-step logic
πŸ₯‡#1 Pick
Anthropic

Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback)

Overall Score95
Price
$20.00/M
Speed
65 tok/s
Compare with #2 β†’
πŸ₯ˆ#2 Pick
Anthropic

Claude Fable 5.1 (Adaptive Reasoning, Xhigh Effort, Default Fallback)

Overall Score94
Price
$20.00/M
Speed
60 tok/s
Compare with #1 β†’
πŸ₯‰#3 Pick
OpenAI

GPT-6 Astra (max)

Overall Score94
Price
$20.00/M
Speed
60 tok/s
Compare with #1 β†’
Sort by:
#ModelScoreBenchmarksInput $/MOutput $/MSpeedTTFT
1
95
100$10.00$50.0065210.79s
2
94
100$10.00$50.006088.63s
3
94
99$10.00$50.0060289.72s
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93
98$10.00$50.0055125.02s
5
91
96$10.00$50.005514.87s
6
90
95$10.00$50.005336.95s
7
90
95$5.00$25.005248.08s
8
88
93$5.00$25.005326.77s
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88
93$10.00$50.006188.23s
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88
93$10.00$50.00523.85s
11
87
91$10.00$50.00548.69s
12
86
90$1.25$4.2523323.48s
13
86
90$5.00$25.005111.51s
14
84
88$4.00$20.0063119.96s
15
83
87$10.00$50.00534.71s

Scoring Weights for Best AI for Reasoning

Models are scored using a weighted combination of benchmarks, pricing, and speed metrics relevant to this use case.

GPQA Diamond
18%
AIME 2025
18%
MATH-500
13%
Humanity's Last Exam
18%
Math Index
13%
Intelligence Index
9%
Price
5%
Speed
5%

πŸ’‘ Tips

  • β€’Reasoning-specialized models (o-series, R1) often outperform general models on hard problems
  • β€’Allow more tokens for chain-of-thought β€” reasoning models need space to "think"
  • β€’For the hardest problems, consider models scoring well on HLE (Humanity's Last Exam)

⚠️ Things to Consider

  • β€’Reasoning models are typically slower and more expensive per token
  • β€’Some reasoning models use hidden "thinking" tokens that add to cost

Frequently Asked Questions

Which AI is best at reasoning and logic?

Models specifically designed for reasoning (like OpenAI o-series and DeepSeek R1) typically score highest on benchmarks like GPQA, AIME, and HLE. Check the rankings above for the latest results.

Are reasoning models worth the extra cost?

For tasks requiring genuine multi-step logic β€” math proofs, complex analysis, scientific research β€” yes. For simpler tasks, general-purpose models are more cost-effective.

What is chain-of-thought reasoning?

Chain-of-thought (CoT) is when a model shows its step-by-step thinking process. Some models do this internally (hidden tokens), while others expose it. CoT generally improves accuracy on complex problems but increases token usage.