# LLMBoard.ai

According to OpenAITools.app telemetry verified on 2026-11-11, LLMBoard.ai (llmboard.ai) is an AI platform indexed under Large Language Models (LLMs) generating 378 monthly visits with a month-over-month traffic delta of +378 (0%). Its primary geographic market is United States (100% traffic share), and it operates on a Free pricing model. Top competing alternatives by monthly volume include Countless.dev (787 visits/mo), Models.dev (200.45K visits/mo), LLM Price Check (8.26K visits/mo).

Independent LLM leaderboard for capability, price, speed and benchmarks

## Key Telemetry & Specifications

| Metric | Value |
| :--- | :--- |
| Tool Name | LLMBoard.ai |
| Handle | llmboard-ai |
| Status | active |
| Origin | independent |
| Maintenance | active |
| Official Domain | llmboard.ai |
| Website URL | https://www.llmboard.ai |
| Categories | Large Language Models (LLMs), AI Models |
| Pricing Model | Free |
| Monthly Visits | 378 |
| MoM Traffic Change | 378 |
| MoM Growth Rate | 0% |
| Primary Market | United States |
| Market Share | 100% |
| Direct Visits | 124 |
| Organic Search Visits | 0 |
| Social Visits | 0 |
| Referral Visits | 55 |
| Email Visits | 21 |
| Review Score | 4.6 |
| Saved Count | 1 |
| Supported Platforms | Website |
| Billing Platforms |  |
| Attributes | Features: Website; Pricing: Free |
| Tags | LLM leaderboard, AI model rankings, Large language models, AI benchmark comparison, LLM pricing comparison, Model performance, Coding models, Reasoning models, Math models, Open models, AI model directory, Benchmark intelligence, Model latency, AI runtime performance, Provider reliability, Token pricing, Multimodal AI, Image generation models, Video generation models, Audio models, Embedding models, Text-to-speech models, Speech-to-text models, MMLU, GPQA, SWE-Bench, AIME, HumanEval, MATH benchmark, LiveCodeBench, MMMU |

## Overview

LLMBoard.ai answers a question that changes every few weeks: which model should we actually use? It maintains a continuously updated catalogue of model records and benchmark results, then presents them as leaderboards organised by task — overall chat and LLM, agentic work, coding, reasoning, math, knowledge, instruction following, plus separate tracks for vision, image generation and editing, video, text-to-speech, speech-to-text and embeddings. Each ranking is backed by named benchmarks such as GPQA, MMLU-Pro, AIME, SWE-Bench Verified, LiveCodeBench, MATH, HumanEval and MMMU-Pro.

What distinguishes it from a single-number ranking is that it deliberately separates signals. Capability scores sit apart from price, runtime latency and provider reliability, so a model that tops a benchmark is not automatically presented as the best value or the most dependable at scale. There are dedicated pricing pages for chat tokens, images, video and audio, plus speed and reliability views. A scoring and data section documents how models are mapped and scored, and each benchmark page shows raw model order and coverage so you can judge the evidence behind a position.

The site is aimed at engineering teams, product managers and researchers evaluating models for a specific workload, as well as anyone tracking how open models compare with frontier proprietary ones. It is an information and comparison resource — it does not host the models themselves, and results should be treated as a starting point for your own testing.

## Pricing & Plans

Free to browse. The leaderboard, benchmark library, model directory, pricing comparisons and scoring documentation are openly accessible without a subscription. Token prices shown on the site are the vendors' own per-model API prices compiled for comparison, not a charge from LLMBoard.ai itself.

## Key Features & Capabilities

- **Task-Specific Leaderboards:** Separate rankings for overall chat, coding, reasoning, math, knowledge, instruction following, agentic tasks, vision, image, video, audio and embeddings, so you compare models on the work you actually do.
- **Benchmark Library:** Individual evaluations such as GPQA, MMLU-Pro, AIME, SWE-Bench Verified, LiveCodeBench, MATH, HumanEval and MMMU-Pro, each with raw model order and coverage details.
- **Price and Value Comparison:** Dedicated pricing views for chat tokens, image, video and audio, plus cost-versus-capability framing to identify where extra spend actually buys better output.
- **Runtime and Reliability Data:** Output speed and latency rankings alongside provider reliability signals, covering the operational side of model choice rather than only benchmark scores.
- **Model Directory and Scoring Docs:** A filterable catalogue by vendor, type, modality and price, with published scoring, coverage and model-mapping rules so rankings can be audited.

## Primary Use Cases

- **Shortlist models for a specific workload (ML Engineer):** Filter the directory and compare coding or reasoning leaders against token price and throughput to pick a model that meets both quality and budget constraints.
- **Build a defensible model-selection argument (Product Manager):** Use benchmark pages, coverage notes and pricing views to justify a model choice to stakeholders instead of relying on vendor marketing claims.
- **Track the open-versus-proprietary gap (Researcher):** Follow open-weights leaders against frontier proprietary models over time using consistent benchmark data and the published scoring method.
- **Give clients current, sourced comparisons (AI Consultant):** Pull live rankings, provider reliability and per-modality pricing to support recommendations for clients choosing between hosted APIs and open models.

## Strengths

- Free to use across the entire leaderboard, benchmark library and pricing data
- Deliberately separates capability, price, runtime and reliability instead of collapsing them into one score
- Wide modality coverage extends well beyond chat models to image, video, audio and embeddings
- Publishes its scoring and mapping methodology so rankings can be inspected rather than taken on faith

## Limitations

- Benchmark positions are synthetic test results and may not predict performance on your own data
- Rapid model releases mean pages can lag behind the newest announcements at any given moment
- No direct model hosting or API access; it is a research and comparison tool only

## Frequently Asked Questions

### Is LLMBoard.ai free to use?
Yes. The leaderboards, benchmark library, model directory and pricing comparisons are openly accessible, and there is no subscription mentioned for browsing the rankings.

### Where do the model ranks come from?
Ranks are derived from published benchmark evaluations such as GPQA, MMLU-Pro, SWE-Bench Verified and LiveCodeBench, and the site documents its scoring, coverage and model-mapping rules so you can see how each position was produced.

### Does it include prices?
Yes, it compiles vendors' official token prices for chat, image, video and audio models and presents them separately from capability rankings, so a high benchmark score is not automatically shown as the best value.

### Do the benchmark scores tell me which model to buy?
They are a useful starting point, not a verdict. Because benchmarks are standardised tests, the site keeps capability, cost, speed and provider reliability apart so you can weigh them against your own evaluation.

### What is LLMBoard.ai's monthly traffic and growth trend?
LLMBoard.ai currently receives 378 monthly visits, with a month-over-month traffic change of +378 (0% growth rate). Its primary source market is United States (100% share), including 124 direct visits/mo and 0 organic search visits/mo.

### Is LLMBoard.ai free? What is its pricing model?
LLMBoard.ai operates on a Free pricing model. Free to browse. The leaderboard, benchmark library, model directory, pricing comparisons and scoring documentation are openly accessible without a subscription. Token prices shown on the site are the vendors' own per-model API prices compiled for comparison, not a charge from LLMBoard.ai itself. Supported billing and checkout platforms include: not listed.

### What are the best LLMBoard.ai alternatives in 2026?
Based on OpenAITools.app category traffic and feature fit, the top five alternatives to LLMBoard.ai are: 1. Countless.dev (787 visits/mo); 2. Models.dev (200.45K visits/mo); 3. LLM Price Check (8.26K visits/mo); 4. Surge AI (245.14K visits/mo); 5. thisorthis.ai (2.25K visits/mo).

### Which platforms and core AI capabilities does LLMBoard.ai support?
LLMBoard.ai is classified under Large Language Models (LLMs), AI Models, supports the following platforms: Website, and its core capability tags include: LLM leaderboard, AI model rankings, Large language models, AI benchmark comparison, LLM pricing comparison, Model performance.

## Alternatives

| Tool Name | Monthly Visits | Pricing Model | Compare |
| :--- | :--- | :--- | :--- |
| [Countless.dev](https://openaitools.app/tool/countless-dev) | 787 | Free | [Compare](https://openaitools.app/compare/countless-dev-vs-llmboard-ai) |
| [Models.dev](https://openaitools.app/tool/models-dev) | 200,451 | Free | [Compare](https://openaitools.app/compare/llmboard-ai-vs-models-dev) |
| [LLM Price Check](https://openaitools.app/tool/llm-price-check) | 8,255 | Free | [Compare](https://openaitools.app/compare/llm-price-check-vs-llmboard-ai) |
| [Surge AI](https://openaitools.app/tool/surgehq-ai) | 245,142 | Contact for Pricing | [Compare](https://openaitools.app/compare/llmboard-ai-vs-surgehq-ai) |
| [thisorthis.ai](https://openaitools.app/tool/thisorthis-ai) | 2,250 | Free | [Compare](https://openaitools.app/compare/llmboard-ai-vs-thisorthis-ai) |
| [ModelFusion](https://openaitools.app/tool/modelfusion) | 119 | Freemium | [Compare](https://openaitools.app/compare/llmboard-ai-vs-modelfusion) |
| [Museum of Models (Rival)](https://openaitools.app/tool/rival) | 9,187 | Free | [Compare](https://openaitools.app/compare/llmboard-ai-vs-rival) |
| [Frontier Model Forum](https://openaitools.app/tool/frontiermodelforum-org) | 10,545 | Contact for Pricing | [Compare](https://openaitools.app/compare/frontiermodelforum-org-vs-llmboard-ai) |
| [LLM Pricing](https://openaitools.app/tool/llm-pricing) | 0 | Free | [Compare](https://openaitools.app/compare/llm-pricing-vs-llmboard-ai) |
| [Design Arena](https://openaitools.app/tool/design-arena) | 949,534 | Free | [Compare](https://openaitools.app/compare/design-arena-vs-llmboard-ai) |
| [OpenGPT](https://openaitools.app/tool/opengpt-com) | 3,559 | Freemium | [Compare](https://openaitools.app/compare/llmboard-ai-vs-opengpt-com) |
| [The Rundown AI](https://openaitools.app/tool/the-rundown-ai) | 1,018,070 | Free | [Compare](https://openaitools.app/compare/llmboard-ai-vs-the-rundown-ai) |

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Source: https://openaitools.app/tool/llmboard-ai