Kimi K2 Thinking Turbo vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Kimi K2 Thinking Turbo by Moonshot AI against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.
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Kimi K2 Thinking Turbo
Motor de Razonamiento ProfundoKimi K2 Thinking Turbo de Moonshot AI es un modelo de IA diseñado para razonamiento lógico profundo, matemáticas avanzadas y resolución científica paso a paso, con ventana de contexto de 262K, velocidad de 90 tokens/s, índice de inteligenci
$0.60 / 1M
$2.40 / 1M
262.1K tokens
N/A
GPT-6 Astra
Modelo de Voz y Audio NativoGPT-6 Astra de OpenAI es un modelo de IA diseñado para síntesis de voz natural, transcripción acústica y procesamiento de audio en tiempo real, con ventana de contexto de 272K, velocidad de 100 tokens/s, índice de inteligencia de 96/100 y t
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Diferencias Clave de un Vistazo
- Kimi K2 Thinking Turbo is 19.5x cheaper for API usage (input + output tokens combined).
- GPT-6 Astra has a larger context window (272K vs 262K tokens).
- GPT-6 Astra is faster at 100 tok/s vs 90 tok/s.
| Característica | Kimi K2 Thinking Turbo | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 84 | 96 |
Provider | Moonshot AI | OpenAI |
Input Price Cost per million input tokens | $0.60 / 1M | $10.00 / 1M |
Output Price Cost per million output tokens | $2.40 / 1M | $50.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.40 / 1M | $7.70 / 1M |
Context Window Maximum input + output tokens | 262.1K tokens~393 A4 pages of text | 272K tokens~408 A4 pages of text |
Max Output Tokens Per single request | 16K | 128K |
Throughput Speed Tokens generated per second | 90 tok/s | 100 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 82.4% |
GPQA Diamond Graduate-level reasoning | 68.5% | 80.9% |
Cached Input Price Prompt caching discount per 1M tokens | $0.06 / 1M | $1.00 / 1M |
¿Quién gana en cada área?
At-a-glance decision frameworkEvaluations ongoing
Puntuaciones 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.
Kimi K2 Thinking Turbo · Strengths & Key Advantages
- Ventana de contexto de 262K con hasta 16K tokens de salida máxima (GPQA Diamond 68.5% · MMLU-Pro 81.5%)
- Rendimiento ágil de 90 tokens/segundo con latencia inicial (TTFT) de solo 520 ms
- Economía de API competitiva ($0.6/$2.4 por 1M de tokens) con soporte para caché de prompts y salidas JSON estructuradas
Considerations & Trade-offs
- Modelo propietario en la nube; no permite descargar los pesos para ejecución local sin conexión
- En demostraciones científicas extremas, los modelos de razonamiento pesado de gama alta ofrecen mayor profundidad
GPT-6 Astra · Strengths & Key Advantages
- Ventana de contexto de 272K con hasta 128K tokens de salida máxima (SWE-bench Verified 82.4% · GPQA Diamond 80.9%)
- Rendimiento ágil de 100 tokens/segundo con latencia inicial (TTFT) de solo 950 ms
- Economía de API competitiva ($10/$50 por 1M de tokens) con soporte para caché de prompts y salidas JSON estructuradas
Considerations & Trade-offs
- Modelo propietario en la nube; no permite descargar los pesos para ejecución local sin conexión
- En volúmenes masivos de tokens, se recomienda activar el caché de prompts y Batch API para optimizar costos
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Kimi K2 Thinking Turbo | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.18 | $2.15 |
Output Tokens / Task Tokens generated per task | 22K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 10K | 32K |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | Kimi K2 Thinking Turbo | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | kimi-k2-thinking-turbo | gpt-6-astra |
| API Protocol | Moonshot AI REST API (OpenAI-Compatible) | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-11 | 2026-09 |
| Knowledge Cutoff | September 2025 | June 2026 |
| Architecture | Hosted Accelerated Reasoning Engine | Omni-Adaptive Autoregressive with Dynamic CoT |
| Parameters | Confidential | 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) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.6/1M in) across full 262K window | Flat rate ($10/1M in) across full 272K window |
| Prompt Cache Policy & TTL | Cached input at $0.06/1M tokens | Automatic prefix caching at $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 | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | 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) | 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 | Moonshot AI 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 | text, vision, audio |
| Output Modalities | text | text, audio |
Kimi K2 Thinking Turbo vs GPT-6 Astra: Respuestas Rápidas (FAQ)
Which is more intelligent, Kimi K2 Thinking Turbo or GPT-6 Astra?
GPT-6 Astra is more intelligent. It scores 96 compared with 84 on the composite Intelligence Index.
Which model is faster?
GPT-6 Astra is faster, generating 100 tokens per second compared with 90 tokens per second.
Which model is cheaper to run?
Kimi K2 Thinking Turbo is cheaper at $0.40 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Kimi K2 Thinking Turbo has lower latency, with a time to first token of 0.52s compared with 0.95s.
Which model has a larger context window?
GPT-6 Astra has a larger context window, supporting 272K tokens compared with 262.1K tokens.
Veredicto
Choose Kimi K2 Thinking Turbo for ideal para razonamiento lógico profundo, matemáticas avanzadas y resolución científica paso a paso, sistemas rag empresariales y automatización mediante api., or choose GPT-6 Astra for ideal para síntesis de voz natural, transcripción acústica y procesamiento de audio en tiempo real, sistemas rag empresariales y automatización mediante api..
Preguntas frecuentes
Which is cheaper: Kimi K2 Thinking Turbo or GPT-6 Astra?+
Kimi K2 Thinking Turbo costs $0.6/1M input and $2.4/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.
Which model has a larger context window: Kimi K2 Thinking Turbo or GPT-6 Astra?+
Kimi K2 Thinking Turbo supports 262K tokens whereas GPT-6 Astra supports 272K 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: Moonshot AI & OpenAI Official Documentation