Grok 4, developed by Elon Musk’s xAI, has rapidly emerged as a top-tier large language model (LLM) in 2025. Positioned to compete with models like GPT-4o, Claude Opus 4, and Gemini 2.5 Pro, Grok 4 delivers breakthrough performance—especially in reasoning, STEM tasks, and academic problem-solving.
The model’s “Heavy” multi-agent configuration has set new records on multiple evaluation benchmarks, challenging the dominance of more established LLMs and redefining what’s possible in high-level AI reasoning.
Here’s how Grok 4 (both standard and Heavy variants) performs across major industry benchmarks compared to leading competitors:
| Benchmark/Test | Grok 4 | Grok 4 Heavy | GPT-4o | Claude Opus 4 | Gemini 2.5 Pro |
|---|---|---|---|---|---|
| Humanity’s Last Exam (HLE) | 25–27% | 41–51% | 22% | 18% | 21–22% |
| ARC-AGI-2 (Reasoning) | 16% | — | 8% | 8% | 7% |
| GPQA (Graduate Science) | 87–88% | 88.9% | 86.4% | 84% | 86.4% |
| AIME 2025 (Math Olympiad) | — | 95–100% | 88.9% | 75.5% | 88.9% |
| SWE-Bench (Coding) | — | 72–75% | 71.7% | 72.5% | 69% |
| USAMO 2025 (Math Olympiad) | — | 61.9% | 34.5% | — | 34.5% |
ARC-AGI-2: Grok 4 achieved a record-setting 16% accuracy, double the performance of GPT-4o and Claude Opus.
Humanity’s Last Exam (HLE): Grok 4 Heavy scored up to 50.7%, a leap beyond any commercial model. The standard version also outperformed GPT-4o and Gemini.
Math Mastery: Grok 4 Heavy scored 95–100% on the AIME 2025 and over 60% on USAMO, making it the most capable math model publicly tested.
Science Proficiency: On GPQA, a graduate-level science benchmark, Grok 4 nearly hit 89%, outperforming Claude and matching GPT-4o.
Coding Skills: Grok 4 Heavy leads on SWE-Bench, with up to 75% pass rate on software engineering tasks.
The Heavy configuration uses multiple agents that work together to solve problems, similar to AI swarms. This setup:
Boosts performance on complex, multi-step tasks
Mimics human collaboration, increasing reasoning depth
Enables superior outcomes in competitive math and logic tests
Grok 4 integrates directly with X (formerly Twitter), giving it access to:
Live event information
Trending discussions
Up-to-the-minute social and political data
This makes Grok uniquely suited for real-time decision-making tasks that other models (e.g., GPT-4 or Claude) can't natively perform.
Its performance on ARC-AGI-2 and HLE suggests Grok 4 is advancing toward AGI-aligned problem-solving, showing not just memorization but adaptive reasoning.
Despite its standout results, Grok 4 has areas where it lags behind or raises concerns:
Grok 4’s vision capabilities are underdeveloped.
It performs poorly on visual benchmarks, especially compared to GPT-4’s multimodal features.
While 256K tokens is large, GPT-4 Turbo and Gemini offer up to 1M tokens.
Grok 4 may struggle with extremely large codebases or documents that exceed this limit.
The Grok 4 Heavy plan costs $300/month, placing it among the most expensive consumer AI tiers.
While justified for research or enterprise, it may not be accessible for casual users or small teams.
| Category | Grok 4 | GPT-4 | Claude Opus | Gemini 2.5 Pro |
|---|---|---|---|---|
| Reasoning | ✅ Industry-leading | Strong | Moderate | Moderate |
| Math & Coding | ✅ Best in class (Heavy) | Very good | Solid | Good |
| Real-Time Info | ✅ Yes (X integration) | ❌ Plugin-dependent | ❌ No | ✅ Partial |
| Multimodal Support | ⚠️ Limited | ✅ Advanced | ✅ Strong | ✅ Advanced |
| Price (Full Access) | ❌ Expensive | Moderate | Moderate | Varies |
Grok 4 Benchmarks Reddit: Community Insights and Reactions
The Reddit community has been actively discussing Grok 4’s benchmark performance, especially its Heavy configuration, which is gaining recognition for delivering record-setting results in reasoning, STEM, and coding evaluations. According to multiple threads and user analyses, Grok 4 Heavy has significantly outperformed competitors like Gemini 2.5 Pro and Claude Opus 4 on key academic tests.
| Benchmark/Test | Grok 4 Heavy Score | Notable Comparisons |
|---|---|---|
| Humanity’s Last Exam (HLE) | 44–45% | Gemini 2.5 Pro: 21% |
| ARC-AGI v2 (Reasoning) | 15.9% | Highest known public score |
| USAMO 2025 (Math Olympiad) | 61.9% | Gemini 2.5 Pro: 34.5% |
| GPQA (Graduate Science) | ~89% | Higher than Claude Opus 4 |
Users describe Grok 4’s USAMO score as a "remarkable leap," and its HLE performance as nearly doubling the prior state-of-the-art for commercial models.
Mathematical and Logical Superiority: Widely considered state-of-the-art in logic-heavy benchmarks.
Bug Detection & Code Analysis: Performs well in SWE-Bench, with users noting success in identifying complex bugs.
Speed vs. Opus: Some users report faster completion times and better price-per-query balance on specific workloads.
Real-World Application Gaps: While Grok 4 excels in controlled benchmarks, many users say it struggles in practical scenarios—especially in:
Following multi-step instructions
Large-scale codebase manipulation
Frontend/UI development
Weak Image & OCR Capabilities: Users note frequent failures in visual tasks, placing Grok behind GPT-4 and Claude in image analysis and document parsing.
Rate Limits: Standard plan users are limited to 20 prompts every 2 hours, frustrating those trying to use Grok for active work.
Prompt Sensitivity: Redditors report Grok 4 is very sensitive to prompt wording, often generating incorrect or off-topic responses with minor phrasing changes.
Frontend Performance: In crowd-ranked frontend development tests, Grok 4 lags behind Grok 3 and Claude, with users citing weak UI output.
Grok 4 Heavy ($300/month): Generally considered worth it only for elite use cases—such as research, high-level planning, or academic benchmarks.
Standard Tier ($30/month): Mixed reviews. Some users say it outperforms Gemini’s free tier, while others claim it under-delivers compared to ChatGPT or Claude.
“Grok 4 Heavy recorded an impressive 61.9% on USAMO. This represents a remarkable increase for such a challenging assessment.”
“Paid $30 for Grok-4, it failed all my personal benchmarks… I feel like I've been scammed.”
“Excellent at planning/architecture, but I switch back to Gemini for implementation when context gets high.”
“It ranks 10th in the frontend dev leaderboard—behind Grok 3 and both Claude models.”
Yes—for STEM, reasoning, and coding.
Grok 4—especially in its Heavy configuration—sets the bar for math, logic, science, and multi-agent task solving. It outperforms GPT-4, Claude Opus, and Gemini Pro in most academic and reasoning benchmarks.
However, Grok 4 falls short in:
Visual capabilities
Reliability in basic tasks
Cost-effectiveness for casual users
Bottom Line: If you're looking for cutting-edge AI performance in STEM, research, or reasoning-heavy use cases, Grok 4 is currently unmatched. But if you need safer outputs, image understanding, or general productivity, GPT-4 or Claude may offer better balance.
Grok 4’s scaling strategy is centered on:
Multi-agent collaboration (via Grok 4 Heavy)
Task specialization
Large-context comprehension (256K tokens)
This modular, agent-based approach enhances complex reasoning, planning, and problem-solving, particularly in benchmarks that require multi-step logic, such as Humanity’s Last Exam (HLE) and USAMO. The model’s performance scales not just with data and compute, but with architectural enhancements like agent orchestration, leading to more accurate and coordinated responses.
| Aspect | Grok 4 (Standard) | Grok 4 Heavy (Multi-Agent) |
|---|---|---|
| Architecture | Single model | Multiple specialized agents |
| Performance | Strong baseline scores | Often 20–100% higher on key tests |
| Use Cases | General use | Research, coding, STEM, enterprise |
| Example (HLE Score) | 25–27% | 44–51% |
| Cost | $30/month | $300/month |
Grok 4 Heavy uses tool use, delegation across agents, and specialized reasoning chains to outperform the standard model significantly in structured evaluations.
The Humanity’s Last Exam (HLE) is designed to assess general intelligence and abstract reasoning. Grok 4 excels due to:
Advanced reasoning chains
Task decomposition across agents
Live-data access, allowing up-to-date, contextual decision-making
Grok 4 Heavy’s multi-agent orchestration allows it to split complex HLE questions into manageable parts, improving consistency and depth of responses—surpassing Gemini, GPT-4o, and Claude Opus significantly.
Tool use and multi-agent strategies allow Grok 4 to:
Simulate collaborative reasoning, mimicking human group problem-solving
Use specialized agents for math, logic, retrieval, or planning
Reduce hallucination by checking and verifying outputs internally
This setup improves performance on complex tasks like:
Math Olympiads (AIME, USAMO)
Advanced reasoning (ARC-AGI v2)
Software engineering tasks (SWE-Bench)
Grok 4’s results suggest that:
General AI is nearing human-level competence in specific academic domains
Multi-agent LLMs are effective scaling strategies
AI may soon assist in real scientific research, coding, and complex diagnostics
The perfect score on AIME and near-90% on GPQA shows that AI can match or exceed graduate-level proficiency in technical subjects—a significant milestone in applied AI.
Across platforms like ARC-AGI, SWE-Bench, GPQA, and HLE, Grok 4 consistently:
Leads or ranks in the top 2 among all public models
Outperforms GPT-4o in math, logic, and reasoning tasks
Falls behind in visual and multimodal evaluations
Grok 4’s strength is clearest in structured, logic-heavy benchmarks, but it lags behind Claude Opus 4 or Gemini DeepThink on language nuance, creativity, and vision tasks.
Multi-agent architecture with parallel tool invocation
Increased compute cost for orchestration and validation
Early access to experimental features (e.g., video generation)
Higher usage limits and enhanced safety tuning for enterprise use
These features are resource-intensive and designed for power users, research institutions, or large-scale enterprise environments—justifying the $300/month price tag.
Gemini DeepThink (internal version) is stronger in:
Visual reasoning and multimodal tasks
Prompt flexibility and user experience
Cross-domain generalization
Grok 4, in contrast, focuses heavily on STEM and logic, and lacks mature image processing or advanced multimodal capabilities—leaving it behind in areas like:
Document OCR
Image-question answering
Spatial reasoning
They enhance:
Decomposition: Breaking down problems into subtasks
Specialization: Routing tasks to domain-specific submodels
Verification: Reducing hallucinations via agent cross-checking
This leads to higher accuracy, especially in math and science, and positions Grok 4 Heavy as a benchmark leader in structured evaluation tasks.
To stay competitive, Grok 4 could improve by:
Expanding multimodal capabilities (vision, audio, video)
Enhancing memory and instruction-following in long sessions
Reducing cost barriers or introducing usage-based pricing tiers
Improving UI/frontend task performance
Increasing transparency and governance, which currently lags behind OpenAI and Google
These upgrades would allow Grok 4 to move beyond benchmark supremacy and become a more holistic, real-world AI assistant.