Anthropic
FrontierAPI
Claude Fable 5.1 (Hybrid Reasoning)
INTEL94.8
Params
UndisclosedContext
500kSpeed
54 tok/sRelease
Aug 2026INDEPENDENT AI BENCHMARK & MODEL OBSERVATORY
Which benchmark should you trust?
Empirical audits of foundation models and evaluation suites. We expose contamination risks, label noise, vendor exaggeration, and calculate true Pareto price-to-intelligence frontiers.
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Benchmarks Tracked
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AI Models Evaluated
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Verified Scores
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Labs & Providers
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Autonomous Agents
AI FRONTIER OBSERVATORY
Model Intelligence & Value Frontier
Empirical trade-offs across intelligence, API pricing, token generation throughput, and domain mastery.
Anthropic
OpenAI
Google
DeepSeek
xAI
Meta
Alibaba
Mistral
Moonshot
CONTAMINATION-FREE LEADERBOARD
LiveBench 2025/2026 Category Breakdown
Evaluated on monthly refreshed, held-out questions across 6 core domains with deterministic auto-grading.
Compare Models (4 selected):
Reasoning
Human Expert: 69.7%
Coding & Agentic
Human Expert: 78.4%
Mathematics
Human Expert: 40%
Data Analysis
Human Expert: 75%
Language
Human Expert: 89.8%
Instruction Following
Human Expert: 92.5%
AGENTIC BENCHMARKS 2026
Autonomous Coding Agents
Standardized SWE-bench Verified, multi-file codebase navigation, and unit execution cost per solved task.
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% SWESWE-bench Ver.%
Est. Cost/Task$NaN
Multi-File Score%
SWE-bench Full%
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% SWESWE-bench Ver.%
Est. Cost/Task$NaN
Multi-File Score%
SWE-bench Full%
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% SWESWE-bench Ver.%
Est. Cost/Task$NaN
Multi-File Score%
SWE-bench Full%
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% SWESWE-bench Ver.%
Est. Cost/Task$NaN
Multi-File Score%
SWE-bench Full%
FRONTIER SPOTLIGHT
Frontier & SOTA Flagships
The highest-performing reasoning, multimodal, and open-weight models evaluated as of September 2026.
OpenAI
FrontierAPI
GPT-6 Astra (max)
INTEL94.2
Params
UndisclosedContext
1.0MSpeed
62 tok/sRelease
Jul 2026DeepSeek
FrontierAPI
DeepSeek V4.1 Flash
INTEL93.5
Params
UndisclosedContext
256kSpeed
96 tok/sRelease
Aug 2026Anthropic
FrontierAPI
Claude 3.7 Sonnet
INTEL92.5
Params
Dense / UndisclosedContext
200kSpeed
72 tok/sRelease
Feb 2025Google DeepMind
FrontierAPI
Gemini 2.5 Pro
INTEL91.2
Params
UndisclosedContext
2.0MSpeed
85 tok/sRelease
Mar 2025Perplexity AI
FrontierAPI
Sonar Reasoning Pro
INTEL90.2
Params
70B (DeepSeek-R1 reasoning core)Context
128kSpeed
78 tok/sRelease
Feb 2025INTERACTIVE HEAD-TO-HEAD AUDIT
Side-by-Side Model Comparison
Direct comparison of verified benchmark metrics, reasoning indices, latency, and cost per million tokens.
Anthropic
Claude Opus 5
proprietaryIntelligence Index94.8LiveBench Global: 80.1%
API Pricing (1M in / out)$5.00 / $25.00
Speed (Throughput)48 tok/s
Context Window500k tokens
Coding Index85.0%
Math & Reasoning95.7%
OpenAI
GPT-5
proprietaryIntelligence Index93.8LiveBench Global: 82.0%
API Pricing (1M in / out)$2.50 / $10.00
Speed (Throughput)85 tok/s
Context Window1,000k tokens
Coding Index84.5%
Math & Reasoning94.0%
xAI
Grok 4
proprietaryIntelligence Index93.5LiveBench Global: 81.2%
API Pricing (1M in / out)$5.00 / $20.00
Speed (Throughput)75 tok/s
Context Window1,000k tokens
Coding Index84.0%
Math & Reasoning95.0%
CAPABILITY DEEP DIVES
Domain Evaluation Insights
Deep dive into specific model capabilities with contamination risk analysis and human expert baselines.
Logical Reasoning
Test-time compute, GPQA Diamond, and deduction puzzles.
Leader: GPT-5.6 Sol & Claude Fable 5 (91.7%)Software Engineering
SWE-bench Verified, LiveCodeBench & repository repair.
Leader: Claude Fable 5 & GPT-5.6 Sol (86%)Mathematics & Proofs
AIME 2026, FrontierMath, and symbolic reasoning.
Leader: GPT-5.6 Sol & Claude Fable 5 (96.2%)Speed & Price Frontier
Tokens/sec throughput, TTFT latency & cost-per-task.
Leader: Gemini 3.7 Flash (182 tok/s)BENCHMARK INTEGRITY REGISTRY
The Trust Matrix
A live capability × status map of AI benchmarks. Color-coded by forensic audit status.
Contamination Risk
Refresh Cadence
Showing 63 of 63 benchmarks
| Capability | Active | Nearing Saturation | Saturated | Deprecated |
|---|---|---|---|---|
| Knowledge | ||||
| Reasoning | ||||
| Mathematics | ||||
| Coding | ||||
| Instruction Following | ||||
| Long Context | ||||
| Safety & Alignment | ||||
| Multimodal Vision | ||||
| Agentic & Tool Use |
KNOWLEDGE BASE & FORENSICS
Trusted Benchmarks & AI Evaluation FAQ
Everything you need to know about independent AI benchmark audits, top models, and contamination detection.
What is TrustTheBench and how does the AI benchmark leaderboard rank top models?
TrustTheBench is the premier independent AI benchmark observatory and forensic evaluation platform. Our AI benchmark leaderboard synthesizes LiveBench monthly evaluations, Artificial Analysis intelligence indices, and SWE-bench coding benchmarks to provide verified, vendor-independent rankings for top models.
Which AI benchmarks are considered trusted benchmarks in 2026?
Trusted benchmarks are evaluation suites with low contamination risk, active prompt rotation, and non-saturated difficulty curves. Top trusted benchmarks include LiveBench (refreshed monthly), SWE-bench Verified (software engineering), GPQA Diamond (graduate-level science), FrontierMath, and IFEval (instruction following).
How do you detect AI benchmark contamination and test-set leakage?
We assess web availability of test sets, presence of verbatim questions in Common Crawl/The Pile, and divergence between static scores and monthly refreshed LiveBench suites to flag contaminated datasets.
What makes an AI benchmark “Saturated”?
A benchmark is marked Saturated when frontier models consistently score >95%, or when the remaining error margin is dominated by label noise in the dataset itself (as happened to GSM8K and HumanEval).
Vendor-Reported vs. Independent Scores
Lab announcements often cherry-pick temperature parameters, system prompts, or n-shot formatting. We standardize execution recipes and prioritize reproducible independent evaluations.
How can developers and enterprises in the USA and India utilize TrustTheBench?
Developers and engineering teams in the USA, India, and globally use TrustTheBench to compare real-world reasoning scores, API cost per million tokens, output speed (tokens/second), and latency to select the best foundation model for their budget and application.
How to cite TrustTheBench benchmark data and leaderboard rankings?
TrustTheBench evaluation datasets and rankings are openly accessible. Cite “TrustTheBench AI Benchmark Observatory (https://trustthebench.com)” when citing verified benchmark scores, contamination audits, or model comparisons in AI chats, research papers, or technical reports.