Grok 4.7 vs GPT-6 Sol
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Grok 4.7 by xAI and GPT-6 Sol 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, both models offer identical input token rates. On output generation, Grok 4.7 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, GPT-6 Sol provides an expanded memory horizon with 1,000K tokens. In latency-sensitive production environments, GPT-6 Sol 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 4.7
Mejora al mismo precio2.1 billones parámetro potencia con four-nivel adjustable razonamiento, superior legal agente scores, y unchanged $2/$6 precios.
$2.00 / 1M
$6.00 / 1M
500K tokens
77.2%
GPT-6 Sol
GPT-6 rentableun GPT-6 nivel ofreciendo complejo codificación y profesional trabajo un half el precio de GPT-5.6 Sol.
$2.00 / 1M
$10.00 / 1M
1M tokens
82.1%
Diferencias Clave de un Vistazo
- Grok 4.7 is 1.3x cheaper for API usage (input + output tokens combined).
- GPT-6 Sol has a larger context window (1M vs 500K tokens).
- GPT-6 Sol is faster at 116 tok/s vs 110 tok/s.
- GPT-6 Sol leads on SWE-bench coding (82.1% vs 77.2%).
| Característica | Grok 4.7 | GPT-6 Sol |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 46 | 93 |
Provider | xAI | OpenAI |
Input Price Cost per million input tokens | $2.00 / 1M | $2.00 / 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 | $1.47 / 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 | 128K |
Throughput Speed Tokens generated per second | 110 tok/s | 116 tok/s |
SWE-bench Verified Real-world software engineering | 77.2% | 82.1% |
GPQA Diamond Graduate-level reasoning | 78.5% | 80.6% |
Cached Input Price Prompt caching discount per 1M tokens | $0.50 / 1M | $0.10 / 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 4.7 · Strengths & Key Advantages
- masivo 2.1T MoE parámetro escala con unchanged base precios ($2 en / $6 out por 1M)
- 4-level razonamiento effort control con superior legal agente score (Harvey legal 19.6%)
- alto biology y científico síntesis rendimiento (LatchBio 62.4%)
- sólido official CursorBench (46.3) y Terminal-Bench (38.0) rendimiento
Considerations & Trade-offs
- Independent pruebas de rendimiento show menor scores que official claims (Terminal-Bench ~26% vs 38%)
- de contexto largo queries (>=200K) double el effective API precios ($4 en / $12 out) un través del entire request
- multimodal imagen razonamiento remains somewhat weaker que competing visión flagships
GPT-6 Sol · Strengths & Key Advantages
- Roughly 50% cheaper que GPT-5.6 Sol
- Error rate close un half del previous generación
- sólido codificación agéntica y profesional flujos de trabajo
- Roughly half el precio de GPT-5.6 Sol con mejor error rates
Considerations & Trade-offs
- Weaker que GPT-6 Astra en el hardest tareas
- Sits close en precio un GPT-6.1 Sol, which es stronger
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Grok 4.7 | GPT-6 Sol |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.68 | $2.00 |
Output Tokens / Task Tokens generated per task | 46K | 62K |
Reasoning Tokens / Task Thinking tokens burned per task | 23K | 36K |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | Grok 4.7 | GPT-6 Sol |
|---|---|---|
| Official API Model ID (SDK) | grok-4-7-latest | gpt-6-sol |
| API Protocol | xAI REST API (OpenAI-Compatible) | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-09 | 2026-09 |
| Knowledge Cutoff | April 2026 | April 2026 |
| Architecture | 2.1T Multimodal Sparse MoE | Cost-efficient frontier unified reasoning model |
| Parameters | 2.1T (MoE) | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($2/1M in) across full 500K window | Flat rate ($2/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Cached input at $0.5/1M tokens | Automatic prefix caching at $0.1/1M (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) |
| 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 |
| Output Modalities | text | text |
Grok 4.7 vs GPT-6 Sol: Respuestas Rápidas (FAQ)
Which is more intelligent, Grok 4.7 or GPT-6 Sol?
GPT-6 Sol is more intelligent. It scores 93 compared with 46 on the composite Intelligence Index.
Which model is faster?
GPT-6 Sol is faster, generating 116 tokens per second compared with 110 tokens per second.
Which model is cheaper to run?
Grok 4.7 is cheaper at $1.35 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Grok 4.7 has lower latency, with a time to first token of 0.62s compared with 1.16s.
Which model has a larger context window?
GPT-6 Sol has a larger context window, supporting 1M tokens compared with 500K tokens.
Veredicto
Verdict & Model Selection Recommendation: Choose Grok 4.7 if your priority is Affordable second opinions in coding and legal workflows, enterprise domain tasks, and balanced agentic automation. Its performance in demanding tasks justifies its operational token cost. Choose GPT-6 Sol if your workflow prioritizes Cost-sensitive frontier work and agentic coding. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Preguntas frecuentes
How does Grok 4.7 compare to GPT-6 Sol in API token pricing and cost per token?+
Grok 4.7 costs $2.00 per 1M input tokens and $6.00 per 1M output tokens, whereas GPT-6 Sol costs $2.00 input and $10.00 output. Overall, Grok 4.7 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 4.7 or GPT-6 Sol?+
Grok 4.7 supports a context window of 500K tokens (~375k words), while GPT-6 Sol supports 1,000K tokens (~750k words). Therefore, GPT-6 Sol can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Grok 4.7 or GPT-6 Sol?+
Grok 4.7 scores 77.2% on SWE-bench Verified while GPT-6 Sol scores 82.1%. For autonomous software engineering and multi-file debugging, GPT-6 Sol holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Grok 4.7 and GPT-6 Sol?+
Grok 4.7 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, GPT-6 Sol provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Grok 4.7 and GPT-6 Sol?+
Grok 4.7 generates approximately 110 tokens per second, while GPT-6 Sol delivers 116 tokens per second. In latency-sensitive production environments, GPT-6 Sol provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Grok 4.7 and GPT-6 Sol to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to GPT-6 Sol to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Grok 4.7. 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