Grok-3 vs GPT-4o
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Grok-3 by xAI and GPT-4o by OpenAI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, GPT-4o holds a notable pricing advantage for token ingestion. On output generation, GPT-4o is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Grok-3 provides an expanded memory horizon with 1,000K tokens. In latency-sensitive production environments, GPT-4o leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
किसी भी मॉडल को बदलें और तुलना करें
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Grok-3
डीप रीजनिंग मॉडलxAI द्वारा विकसित Grok-3 एक उन्नत AI मॉडल है, जिसमें 1M टोकन का कॉन्टेक्स्ट विंडो और $3/1M इनपुट तथा $15/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।
$3.00 / 1M
$15.00 / 1M
1M tokens
65.2%
GPT-4o
फ्लैगशिप फ्रंटियर मॉडलOpenAI द्वारा विकसित GPT-4o एक उन्नत AI मॉडल है, जिसमें 128K टोकन का कॉन्टेक्स्ट विंडो और $2.5/1M इनपुट तथा $10/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।
$2.50 / 1M
$10.00 / 1M
128K tokens
38.8%
एक नज़र में मुख्य अंतर
- GPT-4o is 1.3x cheaper for API usage (input + output tokens combined).
- Grok-3 has a larger context window (1M vs 128K tokens).
- GPT-4o is faster at 105 tok/s vs 95 tok/s.
- Grok-3 leads on SWE-bench coding (65.2% vs 38.8%).
| Feature | Grok-3 | GPT-4o |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 54 | 41 |
Provider | xAI | OpenAI |
Input Price Cost per million input tokens | $3.00 / 1M | $2.50 / 1M |
Output Price Cost per million output tokens | $15.00 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.63 / 1M | $2.38 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 128K tokens~192 A4 pages of text |
Max Output Tokens Per single request | 33K | 16K |
Throughput Speed Tokens generated per second | 95 tok/s | 105 tok/s |
SWE-bench Verified Real-world software engineering | 65.2% | 38.8% |
GPQA Diamond Graduate-level reasoning | 74% | 53.6% |
Cached Input Price Prompt caching discount per 1M tokens | $0.75 / 1M | $1.25 / 1M |
किस क्षेत्र में कौन आगे है?
At-a-glance decision frameworkसत्यापित बेंचमार्क स्कोर तुलना
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
लेटेंसी और रिस्पॉन्स समय
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
रियल-टाइम टोकन लागत सिम्युलेटर
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Grok-3 · Strengths & Key Advantages
- xAI की उन्नत Hybrid Reasoning Deep MoE आर्किटेक्चर और 1M कॉन्टेक्स्ट विंडो क्षमता
- किफायती और पारदर्शी API मूल्य ($3/1M इनपुट, $15/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
- जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
- बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
- विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है
GPT-4o · Strengths & Key Advantages
- OpenAI की उन्नत Omni-Multimodal Dense आर्किटेक्चर और 128K कॉन्टेक्स्ट विंडो क्षमता
- किफायती और पारदर्शी API मूल्य ($2.5/1M इनपुट, $10/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
- जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
- बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
- विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Grok-3 | GPT-4o |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.20 | $0.68 |
Output Tokens / Task Tokens generated per task | 24K | 24K |
Reasoning Tokens / Task Thinking tokens burned per task | 15K | 0K |
तकनीकी विशिष्टताएँ (Specs)
Architecture, release timeline, capabilities, and modalities.
| Feature | Grok-3 | GPT-4o |
|---|---|---|
| Official API Model ID (SDK) | grok-3-latest | gpt-4o |
| API Protocol | xAI REST API (OpenAI-Compatible) | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-02 | 2024-05 |
| Knowledge Cutoff | Late 2024 | October 2023 |
| Architecture | Hybrid Reasoning Deep MoE | Omni-Multimodal Dense |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($3/1M in) across full 1000K window | Flat rate ($2.5/1M in) across full 128K window |
| Prompt Cache Policy & TTL | Cached input at $0.75/1M tokens | Automatic prefix caching at $1.25/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Real-time Web & X (Twitter) Search Grounding + Code Execution | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | xAI Production Safety & Alignment Verified | OpenAI Preparedness Framework Audited & System Card Published |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision | text, vision, audio |
| Output Modalities | text | text, audio |
Grok-3 vs GPT-4o: त्वरित प्रश्नोत्तर (FAQ)
Which is more intelligent, Grok-3 or GPT-4o?
Grok-3 is more intelligent. It scores 54 compared with 41 on the composite Intelligence Index.
Which model is faster?
GPT-4o is faster, generating 105 tokens per second compared with 95 tokens per second.
Which model is cheaper to run?
GPT-4o is cheaper at $2.38 per 1M tokens blended, compared with $2.63 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-4o has lower latency, with a time to first token of 0.41s compared with 1.10s.
Which model has a larger context window?
Grok-3 has a larger context window, supporting 1M tokens compared with 128K tokens.
निष्कर्ष
Verdict & Model Selection Recommendation: Choose Grok-3 if your priority is Frontier algorithmic development, complex technical architecture, and mathematical proofs. Its performance in demanding tasks justifies its operational token cost. Choose GPT-4o if your workflow prioritizes Omni-modal voice applications, conversational agents, and structured enterprise APIs. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
अक्सर पूछे जाने वाले प्रश्न (FAQ)
How does Grok-3 compare to GPT-4o in API token pricing and cost per token?+
Grok-3 costs $3.00 per 1M input tokens and $15.00 per 1M output tokens, whereas GPT-4o costs $2.50 input and $10.00 output. Overall, GPT-4o is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Grok-3 or GPT-4o?+
Grok-3 supports a context window of 1,000K tokens (~750k words), while GPT-4o supports 128K tokens (~96k words). Therefore, Grok-3 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Grok-3 or GPT-4o?+
Grok-3 scores 65.2% on SWE-bench Verified while GPT-4o scores 38.8%. For autonomous software engineering and multi-file debugging, Grok-3 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Grok-3 and GPT-4o?+
Grok-3 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, GPT-4o focuses on standard fast inference.
How does inference speed (tokens per second) compare between Grok-3 and GPT-4o?+
Grok-3 generates approximately 95 tokens per second, while GPT-4o delivers 105 tokens per second. In latency-sensitive production environments, GPT-4o provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Grok-3 and GPT-4o to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to GPT-4o to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Grok-3. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
स्रोत: GetInfoUs Independent AI Benchmarks & Official API Specs