LLM Benchmarks

One transparent Intelligence Index combining public benchmarks with AIMultiple's own agentic, RAG and enterprise-reasoning evaluations.

Last Updated Jun 2026

Methodology

TOP MODEL

Claude Fable 5

Index 92

Best value

MiniMax M3

$0.42 / 1M

Fastest

GPT OSS 120B

0.19s TTFT

Coverage

64 models

8 benchmarks · 336 eval runs

AIMultiple Intelligence Index

Leaderboard

The highest-scoring models across all benchmarks.

#	Model	Index	LegalBench	FinanceReasoning	Text-to-SQL	Agentic RAG	ARC-AGI-2	Agentic LLM Benchmark	FrontierMath	Swe-Bench
1	Claude Fable 5 Anthropic	92	89	90	90	98	-	69	-	-
2	Kimi K3 Moonshot AI	88	86	88	77	93	-	73	-	-
3	GPT-5.6 Sol OpenAI	87	87	90	74	87	93	62	-	-
4	Grok 4.5 X	86	86	88	79	83	-	73	-	-
5	GPT-5.5 OpenAI	83	87	-	-	-	85	59	-	-
6	GPT-5.6 Terra OpenAI	80	85	87	71	91	84	61	-	-
7	GPT-5.6 Sol Pro OpenAI	80	-	91	79	96	-	54	-	-
8	Claude Opus 4.6 Anthropic	78	-	88	68	80	69	72	-	-
9	Gemini 3 Pro Preview Google	77	87	86	60	89	31	-	-	-
10	Gemini 3.1 Pro Preview Google	77	87	87	65	89	77	46	27	-
Page 1 of 7

Cost$20.00

Latency3.98s

Context1M

TTFT3.98s

LegalBench

FinanceReasoning

Text-to-SQL

Agentic RAG

Agentic LLM Benchmark

Cost$6.00

Latency252.11s

Context1M

TTFT252.11s

LegalBench

FinanceReasoning

Text-to-SQL

Agentic RAG

Agentic LLM Benchmark

Cost$11.25

Latency2.47s

Context1M

TTFT2.47s

LegalBench

FinanceReasoning

Text-to-SQL

Agentic RAG

ARC-AGI-2

Agentic LLM Benchmark

Cost$3.00

Latency10.26s

Context500k

TTFT10.26s

LegalBench

FinanceReasoning

Text-to-SQL

Agentic RAG

Agentic LLM Benchmark

Cost$11.25

Latency1.03s

Context272k

TTFT1.03s

LegalBench

ARC-AGI-2

Agentic LLM Benchmark

Cost$5.63

Latency1.92s

Context1M

TTFT1.92s

LegalBench

FinanceReasoning

Text-to-SQL

Agentic RAG

ARC-AGI-2

Agentic LLM Benchmark

Cost$11.25

Latency11.46s

Context1M

TTFT11.46s

FinanceReasoning

Text-to-SQL

Agentic RAG

Agentic LLM Benchmark

Cost$10.00

Latency1.75s

Context1M

TTFT1.75s

FinanceReasoning

Text-to-SQL

Agentic RAG

ARC-AGI-2

Agentic LLM Benchmark

Cost$4.50

Latency-

Context1M

TTFT

LegalBench

FinanceReasoning

Text-to-SQL

Agentic RAG

ARC-AGI-2

Cost$4.50

Latency33.83s

Context1M

TTFT33.83s

LegalBench

FinanceReasoning

Text-to-SQL

Agentic RAG

ARC-AGI-2

Agentic LLM Benchmark

FrontierMath

Page 1 of 7

Charts

Following "Best Performing" models

Frontier Over Time

Intelligence Index by model release date

Cost vs Performance

Blended cost against Intelligence Index

Model × Benchmark

Top models on selected benchmarks

Methodology

How The Index is Built

The Intelligence Index normalizes each benchmark to a 0-100 scale and averages a model's relative standing across the benchmarks it was evaluated on. Each benchmark below feeds that score.

AIMultiple

FinanceReasoningWe evaluated LLMs on 238 hard questions from the FinanceReasoning benchmark (Hendrycks et al.). This subset targets the most challenging financial reasoning tasks, assessing complex multi-step quantitative reasoning with financial concepts and formulas. Our evaluation employed a custom prompt design and scoring criteria of accuracy and token consumption.

AIMultiple

Text-to-SQLWe used our text-to-SQL benchmark methodology on 24 large language models (LLMs) to assess their performance in SQL command generation:

AIMultiple

Agentic RAGWe conducted a benchmark to assess its performance on routing between multiple databases and generating queries.

AIMultiple

AI MemoryWe benchmarked 11 leading text embedding models, including those from OpenAI, Gemini, Cohere, Snowflake, AWS, Mistral, and Voyage AI, using ~500,000 Amazon reviews. We evaluated each model’s ability to retrieve and rank the correct answer first:

AIMultiple

AI HallucinationWe benchmarked 29 different LLMs with 60 questions to measure their hallucination rates

Public

Humanity's Last ExamAGI

FrontierMathIntelligence

Agentic LLM BenchmarkAgentic LLM Benchmark

Recent Updates

Latest changes to the Intelligence Index, model coverage and AIMultiple benchmark methodology.

Jul 16, 2026

Moonshot AI

Kimi K3

New model added to the AIMultiple Intelligence Index.

Jul 9, 2026

OpenAI

GPT-5.6 Sol

New model added to the AIMultiple Intelligence Index.

Jul 9, 2026

OpenAI

GPT-5.6 Terra

New model added to the AIMultiple Intelligence Index.

Jul 9, 2026

OpenAI

GPT-5.6 Sol Pro

New model added to the AIMultiple Intelligence Index.

Explore LLM Use Cases, Analyses & Benchmarks

Audience Simulation: Can LLMs Predict Human Behavior?

LLM

Benchmark

Jun 22

In marketing, evaluating how accurately LLMs predict human behavior is crucial for assessing their effectiveness in anticipating audience needs and recognizing the risks of misalignment, ineffective communication, or unintended influence. Audience simulation with LLMs enables the modeling of virtual audiences, helping organizations anticipate reactions to content or products without relying on costly surveys or focus…

LLM

Benchmark

Jun 15

AI Gateways for OpenAI: OpenRouter Alternatives

We benchmarked OpenRouter, SambaNova, TogetherAI, Groq, and AI/ML API across three indicators (first-token latency, total latency, and output-token count), with 300 tests using short prompts (approx. 18 tokens) and long prompts (approx. 203 tokens) for total latency. If you plan to use one of these AI gateways, you can: In this benchmark, we compared OpenRouter,…

LLM

Benchmark

Jun 5

Large Language Models in Cybersecurity

We evaluated 7 large language models across 9 cybersecurity domains using SecBench, a large-scale and multi-format benchmark for security tasks. We tested each model on 44,823 multiple-choice questions (MCQs) and 3,087 short-answer questions (SAQs), covering data security, identity & access management, network security, vulnerability management, and cloud security. MCQs (Multiple-Choice Questions) benchmarking: SAQs (Short Answer…

LLM

Insight

May 26

ChatGPT for Customer Service: Top 10 Use Cases

ChatGPT has moved from novelty to infrastructure in customer service. Companies are using it to cut response times, handle volume their teams can’t absorb, and reduce the cost of routine interactions. But results vary sharply depending on how it’s implemented. OpenAI launched GPT-5.2, a materially more capable model that is better at instruction-following, reasoning across…

LLM

Benchmark

Apr 15

LLM Quantization: BF16 vs FP8 vs INT4

We benchmarked Qwen3-32B at 4 precision levels (BF16, FP8, GPTQ-Int8, GPTQ-Int4) on a single NVIDIA H100 80GB GPU. Each configuration was evaluated on 2 benchmarks (~12.2K questions) covering knowledge and code generation, plus 2,000+ inference runs to measure throughput. Int4 is 2.7x faster than BF16 while losing less than 2 points on MMLU-Pro, but code…

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LLM Benchmarks

Leaderboard

Claude Fable 5Anthropic92Index

Kimi K3Moonshot AI88Index

GPT-5.6 SolOpenAI87Index

Grok 4.5X86Index

GPT-5.5OpenAI83Index

GPT-5.6 TerraOpenAI80Index

GPT-5.6 Sol ProOpenAI80Index

Claude Opus 4.6Anthropic78Index

Gemini 3 Pro PreviewGoogle77Index

Gemini 3.1 Pro PreviewGoogle77Index

Charts

How The Index is Built

Recent Updates

Kimi K3

GPT-5.6 Sol

GPT-5.6 Terra

GPT-5.6 Sol Pro

Explore LLM Use Cases, Analyses & Benchmarks

Audience Simulation: Can LLMs Predict Human Behavior?

AI Gateways for OpenAI: OpenRouter Alternatives

Large Language Models in Cybersecurity

ChatGPT for Customer Service: Top 10 Use Cases

LLM Quantization: BF16 vs FP8 vs INT4