With the exponential rise of Large Language Models (LLMs), the race for dominance in reasoning, code generation, math, and multilingual tasks is fiercer than ever. In this detailed benchmark breakdown, we compare some of the top-performing models as of Q2 2025:

Qwen3 Series (235B & 32B)
OpenAI’s GPT-4 class (o1 & o3-mini)
Gemini 2.5 Pro
Deepseek-R1
Grok 3 Beta (X)

📊 Dataset Benchmarks Used

Benchmark	Description
ArenaHard	Hard reasoning and alignment challenges
AIME'24/'25	High school-level math problems from the AIME competition
LiveCodeBench	Programming benchmark for real-time coding problems
CodeForces Elo	Competitive coding Elo-style rating
Aider	Code assistance pass@2 accuracy
LiveBench	Real-world interaction + eval (2024/11/25 snapshot)
BFCL	Complex fact-checking + logic reasoning
MultiIF	Multilingual inference tasks across 8 languages

🧠 Model Performance Highlights

🔹 1. Qwen3-235B-A2 (MoE) – The New Titan

ArenaHard: 95.6 (🔥 Highest score)
CodeForces: 2056 (🎯 Best-in-class dev coding Elo)
LiveCodeBench: 70.7 (beats most rivals)
Strengths: Massive accuracy in math (AIME'25 – 81.5) and logical inference (MultiIF – 71.9)

🔹 2. Gemini 2.5 Pro – Google’s Silent Killer

ArenaHard: 96.4 (🔥 Highest overall)
AIME'24/'25: 92.0 / 86.7 (Best math model)
LiveBench: 82.4 (🏆 Strong real-world performance)
Strengths: Multilingual & Math dominance

🔹 3. OpenAI o1 – The Reliable Performer

CodeForces: 1891 (⚠️ Below Qwen/Gemini)
LiveBench: 75.7
BFCL: 67.8
Strengths: Balanced across reasoning, coding, and logic, but lags in raw math

🔹 4. Deepseek-R1 – The Coding Specialist

CodeForces: 2029 (💪 Strong performance)
LiveCodeBench: 64.3
Weakness: AIME'25: only 70.0 (math performance needs work)

🔹 5. Grok 3 Beta – X’s Experimental Genius

AIME'24: 83.9
LiveCodeBench: 70.6
Strengths: Above-average on complex math + code reasoning

🔹 6. OpenAI o3-mini – Lightweight yet Capable

CodeForces: 2036 (👏 Impressive for mini)
Aider: 53.8 (⚠️ Code gen weaker)
Weaknesses: Low on BFCL & MultiIF

📌 Observations & Analysis

✅ MoE vs Dense: Qwen MoE dominates

Qwen3-235B-A2 uses Mixture of Experts (MoE), balancing compute efficiency with task-specific performance.
Outperforms Qwen3-32B dense variant across every metric, proving MoE's edge.

🎯 Gemini 2.5 Pro: Math & Language Beast

Its performance on AIME and multilingual reasoning is unmatched.
Shows Google DeepMind’s direction: Math + MultiLang = AGI route.

🧩 OpenAI o1/o3: Strong Baseline, But Needs Push

Stable and consistent, but not market-leading in any metric except consistency.
o3-mini holds its ground despite being a smaller model.

💻 Coding: Qwen3 > Deepseek > Grok > OpenAI

For serious devs (LiveCodeBench & CodeForces), Qwen3 and Deepseek are top choices.

⚡ Conclusion: Who’s Winning the LLM War in 2025?

Best Overall	Best for Devs	Best for Math	Best Lightweight
Qwen3-235B	Qwen3-235B / Deepseek-R1	Gemini 2.5 Pro	OpenAI o3-mini

Qwen3-235B-A2B has emerged as a front-runner in general performance, especially in reasoning and coding. Gemini dominates math and language, while OpenAI models remain versatile and stable.

🧠 Pro Tip for Builders

If you're:

🧑‍💻 a coder → Go with Qwen3 / Deepseek
📚 a researcher → Use Gemini 2.5 Pro
👷‍♂️ building LLM-powered apps → Mix OpenAI + Qwen for reliability + innovation

🔍 Battle of the Titans: Latest LLM Benchmark Comparison (Q2 2025)

Comments

About the Author

Satyam Yadav

Tags

🔍 Battle of the Titans: Latest LLM Benchmark Comparison (Q2 2025)

Comments

About the Author

Satyam Yadav

Tags