Grok 4.1 vs Grok-3
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Grok 4.1 by xAI and Grok-3 by xAI 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, Grok 4.1 holds a notable pricing advantage for token ingestion. On output generation, Grok 4.1 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Grok 4.1 provides an expanded memory horizon with 2,000K tokens. In latency-sensitive production environments, Grok 4.1 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.
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Grok 4.1
Disruptor económicode xAI económico disruptor pairing un masivo 2M-token contexto con ultra-bajo $0.20/1M precios y un 3x menor hallucination rate que Grok 4.0 — construido para alto-volumen cargas de trabajo.
$0.20 / 1M
$1.00 / 1M
2M tokens
66.4%
Grok-3
Rey coloso de fronterade xAI líder modelo de frontera entrenado en 200,000+ Nvidia GPUs, introducing profundo pensamiento deliberation modes, competitivo matemáticas mastery, y nativo codificación agentes.
$3.00 / 1M
$15.00 / 1M
1M tokens
65.2%
Diferencias Clave de un Vistazo
- Grok 4.1 is 15.0x cheaper for API usage (input + output tokens combined).
- Grok 4.1 has a larger context window (2M vs 1M tokens).
- Grok 4.1 is faster at 142 tok/s vs 95 tok/s.
- Grok 4.1 leads on SWE-bench coding (66.4% vs 65.2%).
| Característica | Grok 4.1 | Grok-3 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 51 | 54 |
Provider | xAI | xAI |
Input Price Cost per million input tokens | $0.20 / 1M | $3.00 / 1M |
Output Price Cost per million output tokens | $1.00 / 1M | $15.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.17 / 1M | $2.63 / 1M |
Context Window Maximum input + output tokens | 2M tokens~3,000 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 66K | 33K |
Throughput Speed Tokens generated per second | 142 tok/s | 95 tok/s |
SWE-bench Verified Real-world software engineering | 66.4% | 65.2% |
GPQA Diamond Graduate-level reasoning | 63.8% | 74% |
Cached Input Price Prompt caching discount per 1M tokens | $0.05 / 1M | $0.75 / 1M |
¿Quién gana en cada área?
At-a-glance decision frameworkPuntuaciones de Benchmarks Verificadas
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.
Latencia y Tiempo de Respuesta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interactivo de Costos de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Grok 4.1 · Strengths & Key Advantages
- ultra-bajo precios — up un 25x cheaper que premium flagships
- masivo 2M-token ventana de contexto
- 3x menor hallucination rate que Grok 4.0
- más alto rendimiento en clase (142 tok/s)
Considerations & Trade-offs
- menor pico razonamiento y codificación que superior-3 flagships
- Smaller ecosistema y tooling que OpenAI / Anthropic
Grok-3 · Strengths & Key Advantages
- construido upon el expanded 200K H100/H200 Colossus compute fabric
- Outstanding competitivo programación y AIME mathematics benchmark scores
- 1,000,000 token ventana de contexto con nativo razonamiento effort toggles
Considerations & Trade-offs
- requiere sustancial razonamiento tiempo during extendido pensamiento passes
- mayor empresarial costo por prompt
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Grok 4.1 | Grok-3 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.28 | $0.20 |
Output Tokens / Task Tokens generated per task | 40K | 24K |
Reasoning Tokens / Task Thinking tokens burned per task | 21K | 15K |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | Grok 4.1 | Grok-3 |
|---|---|---|
| Official API Model ID (SDK) | grok-4-1-latest | grok-3-latest |
| API Protocol | xAI REST API (OpenAI-Compatible) | xAI REST API (OpenAI-Compatible) |
| Release Date | 2025-11 | 2025-02 |
| Knowledge Cutoff | 2025 | Late 2024 |
| Architecture | Sparse MoE | Hybrid Reasoning Deep MoE |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.2/1M in) across full 2000K window | Flat rate ($3/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Cached input at $0.05/1M tokens | Cached input at $0.75/1M tokens |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| 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 | Real-time Web & X (Twitter) Search Grounding + Code Execution |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | API Prompt Engineering & RAG Distillation |
| 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) |
| 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 | xAI Production Safety & Alignment Verified |
| 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 |
| Output Modalities | text | text |
Grok 4.1 vs Grok-3: Respuestas Rápidas (FAQ)
Which is more intelligent, Grok 4.1 or Grok-3?
Grok-3 is more intelligent. It scores 54 compared with 51 on the composite Intelligence Index.
Which model is faster?
Grok 4.1 is faster, generating 142 tokens per second compared with 95 tokens per second.
Which model is cheaper to run?
Grok 4.1 is cheaper at $0.17 per 1M tokens blended, compared with $2.63 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Grok-3 has lower latency, with a time to first token of 1.10s compared with 1.50s.
Which model has a larger context window?
Grok 4.1 has a larger context window, supporting 2M tokens compared with 1M tokens.
Veredicto
Verdict & Model Selection Recommendation: Choose Grok 4.1 if your priority is High-volume applications, budget-constrained projects, data extraction, and large-scale prototyping. Its performance in demanding tasks justifies its operational token cost. Choose Grok-3 if your workflow prioritizes Frontier algorithmic development, complex technical architecture, and mathematical proofs. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Preguntas frecuentes
How does Grok 4.1 compare to Grok-3 in API token pricing and cost per token?+
Grok 4.1 costs $0.20 per 1M input tokens and $1.00 per 1M output tokens, whereas Grok-3 costs $3.00 input and $15.00 output. Overall, Grok 4.1 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 4.1 or Grok-3?+
Grok 4.1 supports a context window of 2,000K tokens (~1,500k words), while Grok-3 supports 1,000K tokens (~750k words). Therefore, Grok 4.1 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Grok 4.1 or Grok-3?+
Grok 4.1 scores 66.4% on SWE-bench Verified while Grok-3 scores 65.2%. For autonomous software engineering and multi-file debugging, Grok 4.1 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Grok 4.1 and Grok-3?+
Grok 4.1 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Grok-3 provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Grok 4.1 and Grok-3?+
Grok 4.1 generates approximately 142 tokens per second, while Grok-3 delivers 95 tokens per second. In latency-sensitive production environments, Grok 4.1 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Grok 4.1 and Grok-3 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Grok 4.1 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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Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.
Fuentes: GetInfoUs Independent AI Benchmarks & Official API Specs