StackAI LLM Leaderboard: Comparing Models by Benchmarks and Cost

LinkStackAITool

StackAI provides an interactive dashboard comparing large language models across multiple benchmarks, throughput, context window sizes, and pricing. It compiles evaluation metrics such as MMLU, HumanEval+, GPQA, SWE benchmarks, and GSM8K for side-by-side model comparison.

Key points

  1. Evaluates models across standard benchmarks including MMLU, HumanEval+, GPQA, MT-Bench, SWE, and GSM8K.
  2. Claude 4.7 Opus leads in MMLU score (92.8%), closely followed by GPT-5.5 (92.4%) and Gemini 3 Pro (89.8%).
  3. Mercury 2 by Inception tops throughput with 870.9 tokens/s, ahead of IBM's Granite 4.0 Small at 448.8 tokens/s.
  4. Most cost-effective models per million tokens include Gemma 3n E4B ($0.037 effective) and Llama 3.2 1B Instruct ($0.053 effective).
  5. Grok models (Grok 4 Fast, Heavy, 4.1, 4.20) lead context window capacity with 2,000,000 tokens, alongside GPT 4.1 at 1,280,000 tokens.

Why it matters

Choosing LLMs for real-world software architecture requires balancing raw reasoning capabilities against token pricing, latency, and context sizes. This dashboard provides aggregate comparative data to support those engineering decisions.

Analysis

The leaderboard connects academic benchmark scores with pragmatic deployment metrics such as generation speed and token cost. This highlights the trade-offs between ultra-fast or budget-friendly models and frontier models designed for high-accuracy reasoning.

Mentioned links

Found in

Summary generated by AI (Gemini 3.8 Flash, 27 September 2026). It may contain errors – the original source is authoritative.

Related entries

Similar in content, found by the AI search.

  • Link:clickrank.ai

    LLM Leaderboards in 2026: Benchmarks, Methodologies, and Model Rankings

    A guide by ClickRank AI examines the state of LLM evaluations in 2026. With legacy benchmarks like MMLU and HumanEval largely saturated, evaluation platforms now focus on harder reasoning tests, human pairwise blind comparisons, and composite indices covering cost and latency.

    AI & LLMs· Resource

  • Link:Epoch AI

    Epoch AI launches AI capabilities and benchmarking dashboard

    Epoch AI provides a dashboard tracking and visualising benchmark performance across leading AI models. The platform aggregates Epoch AI's internal evaluations as well as external datasets across fields such as mathematics, software engineering, agents, and multimodal reasoning.

    AI & LLMs· Resource

  • Link:spark-arena.com

    Spark Arena: LLM Performance Leaderboard on NVIDIA DGX Spark

    Spark Arena is a public leaderboard tracking Large Language Model performance on NVIDIA DGX Spark hardware. Powered by open-source tooling, it provides transparent benchmark comparisons across inference engines including vLLM, SGLang, TensorRT-LLM, and llama.cpp.

    AI & LLMs· Tool

Back to the knowledge base

Let's talk about your project

Get in touch

Locations

  • Mattersburg
    Johann Nepomuk Bergerstraße 7/2/14
    7210 Mattersburg, Austria
  • Vienna
    Ungargasse 64-66/3/404
    1030 Wien, Austria

Parts of this content were created with the assistance of AI.