Comprehensive benchmarking results for the latest Large Language Models across multiple performance metrics
Response time and tokens per second measurement
Correctness and reliability across various tasks
Complex problem-solving capabilities
Price per token and overall efficiency
End-to-end response time analysis
Token processing capacity per second
Maximum context window and capacity
Advanced reasoning and computation capabilities
Software engineering and code generation capabilities
Top 5 LLM models with comprehensive performance metrics
Top 5 AI news stories with the same card style as our benchmark results.
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The Benchmark Hub complex reasoning leaderboard rigorously evaluates frontier models across math proofs, coding puzzles, temporal and spatial reasoning, multi-step logic, and abstract problem-solving. Scores come from curated suites, ensemble judges, and consistency checks to highlight systems that stay reliable under varied reasoning workloads.
Model
OpenAI GPT-5
overall_score
92.20%
overall_score
92.20%
Model
xAI Grok 4
overall_score
81.80%
overall_score
81.80%
Evaluates safety-first reasoning under strict constraints and policy guardrails. Models are challenged with red-team style prompts, instruction adherence, refusal accuracy, and boundary conditions to expose brittleness.
Model
OpenAI GPT-5
Overall Score
79.20%
Overall Score
79.20%
Model
OpenAI o3
Overall Score
57.20%
Overall Score
57.20%
Scores story-driven video models on motion consistency, frame coherence, lip sync, text rendering, temporal alignment, and safety filters across varied shot types and prompts.
Model
Veo 3 (w/o audio)
Elo Rating
1267.99
Trust Skill Rating
1178.14
Model
Veo 2
Elo Rating
1135.46
Trust Skill Rating
1065.5
Research briefs and deep dives from our team.
Benchmark Hub provides comprehensive, objective performance analysis of Large Language Models. Our testing methodology ensures fair comparisons across multiple dimensions including speed, accuracy, reasoning capabilities, and cost-effectiveness.
We continuously update our benchmarks to reflect the latest model releases and improvements, helping developers, researchers, and organizations make informed decisions about which LLM best suits their needs.