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Best AI Models for Reasoning in 2026

We test AI models on complex reasoning tasks—tradeoff analysis, strategic planning, root cause diagnosis—so you can find the model that thinks most clearly.

Reasoning benchmarks Source reviewed Analysis depth

Reasoning Leaderboard

Feb 2026
1
Claude Opus 4.7
9.4
2
Kimi K2.5
9.2
3
GLM-5
8.6
4
GPT-5.5
8.5
5
Gemini 3.1 Pro Preview
8.4

Reasoning Model Rankings

Performance scores, pricing, and context windows for reasoning-focused tasks.

Rank Model Score Pricing ($/M) Context Key Strengths
#1
Claude Opus 4.7
Anthropic
9.4/10 $5 / $25 1M Best at nuanced analysis • Excellent tradeoff evaluation • Strong strategic thinking
#2
Kimi K2.5
Moonshot
9.2/10 $2 / $10 200K Top logical reasoning • Great value • Handles complex chains
#3
GLM-5
Zhipu AI
8.6/10 $0.5 / $0.5 128K Strong analysis • Ultra-low cost • Enterprise ready
#4
GPT-5.5
OpenAI
8.5/10 $5 / $30 1M Good general reasoning • Fast responses • Strong ecosystem
#5
Gemini 3.1 Pro Preview
Google
8.4/10 $2 / $12 1M Massive context • Research synthesis • Good multimodal
#6
MiniMax M2.5
MiniMax
8.3/10 $0.5 / $2 245K Budget option • Fast inference • Good for scale

Benchmark Breakdown

How top models perform across specific reasoning tasks (scale: 1-10).

Task Description Claude Kimi GLM-5 GPT
Tradeoff Analysis Evaluating pros/cons of technical decisions 9.5 9.3 8.7 8.4
Root Cause Analysis Diagnosing problems from symptoms 9.4 9.1 8.5 8.6
Strategic Planning Multi-step plans with dependencies 9.3 9.2 8.4 8.3
Logical Deduction Following logical chains to conclusions 9.2 9.4 8.8 8.5
Risk Assessment Identifying and prioritizing risks 9.4 8.9 8.5 8.2
Comparative Analysis Comparing options against criteria 9.5 9 8.6 8.5

When to Use Which Model

Decision guide for picking the right reasoning model for your situation.

Executive decision support

Claude Opus 4.7

Best at nuanced analysis and presenting tradeoffs clearly. Excels at "it depends" scenarios.

Technical architecture decisions

Claude Opus 4.7

Deep understanding of system design tradeoffs and can articulate long-term implications.

High-volume analysis tasks

Kimi K2.5

Excellent reasoning at a fraction of the cost. Strong logical chains for complex analysis.

Budget-constrained projects

GLM-5

Solid reasoning capability at $0.50/$0.50 per million tokens. Best value for analysis tasks.

Research synthesis

Gemini 3.1 Pro Preview

1M context window lets you include extensive background material for comprehensive analysis.

Frequently Asked Questions

What is the best AI model for reasoning in 2026?

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Claude Opus 4.7 currently leads our reasoning benchmarks with a 9.4/10 score, excelling at tradeoff analysis, strategic planning, and nuanced decision support. Kimi K2.5 is a close second at 9.2/10 with better value.

What tasks count as "reasoning" in your benchmarks?

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We test: tradeoff analysis (comparing options), root cause analysis (diagnosing problems), strategic planning (multi-step plans), logical deduction (following chains), risk assessment, and comparative analysis against criteria.

Why does Claude excel at reasoning?

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Claude tends to acknowledge uncertainty, present multiple perspectives, and avoid overconfident assertions. It excels at "it depends" scenarios where context matters more than binary answers.

Is reasoning capability worth paying more for?

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For critical decisions, yes. Better reasoning means fewer costly mistakes and more thorough analysis. For routine tasks, models like Kimi or GLM offer strong reasoning at lower cost.

How do I test reasoning quality myself?

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Give models ambiguous scenarios with no clear right answer. Better reasoning models will acknowledge tradeoffs, ask clarifying questions, and present balanced perspectives rather than confident wrong answers.

See Full Daily Scorecards

Get detailed task-level breakdowns, failure cases, and cost analysis for every model we test.

View scorecards