Grok 4.1 vs GPT-6.1 Sol
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Grok 4.1 by xAI against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.
Cambia y Compara Cualquier Modelo
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Live comparison: no in-depth editorial review has been published for this pair yet.
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%
GPT-6.1 Sol
Valor cercano a Astraofrece results close un GPT-6 Astra un roughly one fifth del precio — el latest 2026 lanzamiento.
$2.00 / 1M
$10.00 / 1M
1M tokens
82.3%
Diferencias Clave de un Vistazo
- Grok 4.1 is 9.5x 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 120 tok/s.
- GPT-6.1 Sol leads on SWE-bench coding (82.3% vs 66.4%).
| Característica | Grok 4.1 | GPT-6.1 Sol |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 51 | 94 |
Provider | xAI | OpenAI |
Input Price Cost per million input tokens | $0.20 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $1.00 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.17 / 1M | $1.47 / 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 | 128K |
Throughput Speed Tokens generated per second | 142 tok/s | 120 tok/s |
SWE-bench Verified Real-world software engineering | 66.4% | 82.3% |
GPQA Diamond Graduate-level reasoning | 63.8% | 80.8% |
Cached Input Price Prompt caching discount per 1M tokens | $0.05 / 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 4.1 · 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
GPT-6.1 Sol · Strengths & Key Advantages
- Near-Astra results un roughly un fifth del costo
- Excellent codificación y de largo alcance agente rendimiento
- sólido reliability con far menor latencia que Astra
- Near-insignia results un roughly un fifth del precio
Considerations & Trade-offs
- Still marginally behind Astra en el muy hardest razonamiento
- Same precio as GPT-6 Sol, so el upgrade decision es easy
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Grok 4.1 | GPT-6.1 Sol |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.28 | $2.05 |
Output Tokens / Task Tokens generated per task | 40K | 62K |
Reasoning Tokens / Task Thinking tokens burned per task | 21K | 36K |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | Grok 4.1 | GPT-6.1 Sol |
|---|---|---|
| Official API Model ID (SDK) | grok-4-1-latest | gpt-6-1-sol |
| API Protocol | xAI REST API (OpenAI-Compatible) | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-11 | 2026-09 |
| Knowledge Cutoff | 2025 | April 2026 |
| Architecture | Sparse MoE | Near-Astra unified reasoning model |
| 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) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.2/1M in) across full 2000K window | Flat rate ($2/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Cached input at $0.05/1M 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 4.1 vs GPT-6.1 Sol: Respuestas Rápidas (FAQ)
Which is more intelligent, Grok 4.1 or GPT-6.1 Sol?
GPT-6.1 Sol is more intelligent. It scores 94 compared with 51 on the composite Intelligence Index.
Which model is faster?
Grok 4.1 is faster, generating 142 tokens per second compared with 120 tokens per second.
Which model is cheaper to run?
Grok 4.1 is cheaper at $0.17 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-6.1 Sol has lower latency, with a time to first token of 1.12s 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
Choose Grok 4.1 for alto-volumen aplicaciones, económico-constrained projects, datos extracción, y grande-escala prototyping, or choose GPT-6.1 Sol for el mejor valor modelo de frontera para profesional y agentic trabajo.
Preguntas frecuentes
Which is cheaper: Grok 4.1 or GPT-6.1 Sol?+
Grok 4.1 costs $0.2/1M input and $1/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: Grok 4.1 or GPT-6.1 Sol?+
Grok 4.1 supports 2M tokens whereas GPT-6.1 Sol supports 1M tokens.
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: xAI & OpenAI Official Documentation