Grok 4.6 vs Grok-4
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Grok 4.6 by xAI and Grok-4 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 4.6 holds a notable pricing advantage for token ingestion. On output generation, Grok 4.6 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Grok-4 provides an expanded memory horizon with 1,000K tokens. In latency-sensitive production environments, Grok-4 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.
Cambia y Compara Cualquier Modelo
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Grok 4.6
Base más grande1.5 billones parámetro Colossus-trained modelo fundacional ofreciendo reinforced codificación y profundo multi-hop razonamiento.
$2.00 / 1M
$6.00 / 1M
500K tokens
75.8%
Grok-4
Coloso de frontera en tiempo realde xAI de frontera multimodal razonamiento system entrenado en el 100k+ H100/H200 Colossus clúster con nativo zero-latencia X stream indexing.
$2.50 / 1M
$10.00 / 1M
1M tokens
76.5%
Diferencias Clave de un Vistazo
- Grok 4.6 is 1.4x cheaper for API usage (input + output tokens combined).
- Grok-4 has a larger context window (1M vs 500K tokens).
- Grok-4 is faster at 125 tok/s vs 115 tok/s.
- Grok-4 leads on SWE-bench coding (76.5% vs 75.8%).
| Característica | Grok 4.6 | Grok-4 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 77 | 92 |
Provider | xAI | xAI |
Input Price Cost per million input tokens | $2.00 / 1M | $2.50 / 1M |
Output Price Cost per million output tokens | $6.00 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $1.35 / 1M | $1.68 / 1M |
Context Window Maximum input + output tokens | 500K tokens~750 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 66K | 64K |
Throughput Speed Tokens generated per second | 115 tok/s | 125 tok/s |
SWE-bench Verified Real-world software engineering | 75.8% | 76.5% |
GPQA Diamond Graduate-level reasoning | 77.2% | 77.8% |
Cached Input Price Prompt caching discount per 1M tokens | $0.50 / 1M | $0.25 / 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 4.6 · Strengths & Key Advantages
- masivo 1.5T parámetro capacidad proporcionando broader real-mundo knowledge y matiz
- Preserves el attractive $2/$6 por millones token precio point
- Notable improvements en completo-stack codificación y multifarchivo system arquitectura
Considerations & Trade-offs
- Quickly succeeded por el 2.1T parámetro Grok 4.7 upgrade
- ventana de contexto capped un 500K tokens
Grok-4 · Strengths & Key Advantages
- Zero-day knowledge síntesis via direct en vivo X feed integración
- ultra-bajo latencia inferencia y alto salida rendimiento (125 tps)
- Uninhibited conversacional tono con reduced corporativo guardrail refusal
- excepcional competitivo matemáticas y codificación rendimiento
Considerations & Trade-offs
- contexto recuperación sobre 800K tokens has minor perimetral-case variance
- menos especializado en niche empresarial legal documentation que Claude Opus
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Grok 4.6 | Grok-4 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.65 | $1.65 |
Output Tokens / Task Tokens generated per task | 45K | 48K |
Reasoning Tokens / Task Thinking tokens burned per task | 22K | 24K |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | Grok 4.6 | Grok-4 |
|---|---|---|
| Official API Model ID (SDK) | grok-4-6-latest | grok-4-latest |
| API Protocol | xAI REST API (OpenAI-Compatible) | xAI REST API (OpenAI-Compatible) |
| Release Date | 2026-08 | 2026-07 |
| Knowledge Cutoff | April 2026 | Real-time (Up to October 2026) |
| Architecture | 1.5T Colossus Sparse MoE | Colossus-Scale Dense Mixture-of-Experts |
| Parameters | 1.5T (MoE) | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($2/1M in) across full 500K window | Flat rate ($2.5/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Cached input at $0.5/1M tokens | Cached input at $0.25/1M tokens |
| 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 | 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 4.6 vs Grok-4: Respuestas Rápidas (FAQ)
Which is more intelligent, Grok 4.6 or Grok-4?
Grok-4 is more intelligent. It scores 92 compared with 77 on the composite Intelligence Index.
Which model is faster?
Grok-4 is faster, generating 125 tokens per second compared with 115 tokens per second.
Which model is cheaper to run?
Grok 4.6 is cheaper at $1.35 per 1M tokens blended, compared with $1.68 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Grok 4.6 has lower latency, with a time to first token of 0.58s compared with 0.68s.
Which model has a larger context window?
Grok-4 has a larger context window, supporting 1M tokens compared with 500K tokens.
Veredicto
Verdict & Model Selection Recommendation: Choose Grok 4.6 if your priority is Medium-to-large software engineering tasks, data synthesis, and complex analysis. Its performance in demanding tasks justifies its operational token cost. Choose Grok-4 if your workflow prioritizes Breaking news analysis, real-time market sentiment, coding, and fast multimodal reasoning. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Preguntas frecuentes
How does Grok 4.6 compare to Grok-4 in API token pricing and cost per token?+
Grok 4.6 costs $2.00 per 1M input tokens and $6.00 per 1M output tokens, whereas Grok-4 costs $2.50 input and $10.00 output. Overall, Grok 4.6 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 4.6 or Grok-4?+
Grok 4.6 supports a context window of 500K tokens (~375k words), while Grok-4 supports 1,000K tokens (~750k words). Therefore, Grok-4 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Grok 4.6 or Grok-4?+
Grok 4.6 scores 75.8% on SWE-bench Verified while Grok-4 scores 76.5%. For autonomous software engineering and multi-file debugging, Grok-4 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Grok 4.6 and Grok-4?+
Grok 4.6 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Grok-4 provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Grok 4.6 and Grok-4?+
Grok 4.6 generates approximately 115 tokens per second, while Grok-4 delivers 125 tokens per second. In latency-sensitive production environments, Grok-4 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Grok 4.6 and Grok-4 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Grok 4.6 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Grok-4. 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