Head-to-Head Model Comparison

Command A Plus vs GPT-6 Astra

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
Compartir
Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Command A Plus vs GPT-6 Astra: Benchmarks, Pricing & Speed Comparison

Command A Plus de Cohere y GPT-6 Astra de OpenAI compiten directamente en el ecosistema actual de IA. Command A Plus ofrece una ventana de contexto de 128K tokens a $3.00/$12.00 por millón de tokens (entrada/salida), mientras que GPT-6 Astra ofrece 272K tokens de contexto a $10.00/$50.00 por millón de tokens. Analizamos sus benchmarks, latencia y costos reales.

Comparación Directa (VS)

Cambia y Compara Cualquier Modelo

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Profile
Profile
Multi-Model Arena Stack:
5-Model Matrix Workbench
Popular Matchups:
Cohere

Command A Plus

Modelo Base de Pesos Abiertos

Command A Plus de Cohere es un modelo de IA diseñado para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, con ventana de contexto de 128K, velocidad de 68 tokens/s, índice de inteligencia de 58/100 y t

Intelligence Index58 / 100
Input Token:

$3.00 / 1M

Output Token:

$12.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

60.5%

OpenAI

GPT-6 Astra

Modelo de Voz y Audio Nativo

GPT-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

Intelligence Index96 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

Diferencias Clave de un Vistazo

  • Command A Plus is 3.7x cheaper for API usage (input + output tokens combined).
  • GPT-6 Astra has a larger context window (272K vs 128K tokens).
  • GPT-6 Astra is faster at 100 tok/s vs 68 tok/s.
  • GPT-6 Astra leads on SWE-bench coding (82.4% vs 60.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaCommand A PlusGPT-6 Astra
Intelligence Index
Composite reasoning & knowledge score (0-100)
5896
Provider
CohereOpenAI
Input Price
Cost per million input tokens
$3.00 / 1M$10.00 / 1M
Output Price
Cost per million output tokens
$12.00 / 1M$50.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$2.33 / 1M$7.70 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text272K tokens~408 A4 pages of text
Max Output Tokens
Per single request
33K128K
Throughput Speed
Tokens generated per second
68 tok/s100 tok/s
SWE-bench Verified
Real-world software engineering
60.5%82.4%
GPQA Diamond
Graduate-level reasoning
74%80.9%
Cached Input Price
Prompt caching discount per 1M tokens
$0.75 / 1M$1.00 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
GPT-6 Astra
+21.9% SWE-bench lead
Costo
Command A Plus
3.7x cheaper monthly runtime
Velocidad
GPT-6 Astra
+47% faster generation
Contexto
GPT-6 Astra
272K tokens window

Puntuaciones de Benchmarks Verificadas

Official evaluation metrics verified by independent third-party research labs.

Command A PlusGPT-6 Astra
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

60.5%vs82.4%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

74%vs80.9%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

86.8%vs89.9%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1410ptsvs1520pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs18.2%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

50%vs63.8%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs54.9%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs79.8%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

82.5%vs93.6%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

88%vs91.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

68 tok/s vs100 tok/s

Latencia y Tiempo de Respuesta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Command A Plus0.56s
GPT-6 Astra0.95s
Est. End-to-End Response (500 tokens)TTFT + generation time
Command A Plus7.91s
GPT-6 Astra5.95s

Simulador Interactivo de Costos de Tokens

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Command A Plus Monthly API Bill
$16.43 / month
$3/1M in · $12/1M out
GPT-6 Astra Monthly API Bill
$61.50 / month
$10/1M in · $50/1M out
Command A Plus saves approximately $45.08 / month (73%) under this workload.3.7x Savings

Command A Plus · Strengths & Key Advantages

  • Ventana de contexto de 128K con hasta 33K tokens de salida máxima (SWE-bench Verified 60.5% · GPQA Diamond 74%)
  • Rendimiento ágil de 68 tokens/segundo con latencia inicial (TTFT) de solo 560 ms
  • Pesos abiertos (Confidential (~180B+ MoE)) listos para autoalojamiento local o en nube privada mediante vLLM y Ollama
Considerations & Trade-offs
  • Requiere infraestructura GPU dedicada con suficiente memoria VRAM para inferencia local sin cuantización
  • En volúmenes masivos de tokens, se recomienda activar el caché de prompts y Batch API para optimizar costos

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.

MetricCommand A PlusGPT-6 Astra
Cost per Task
Estimated USD to finish one task
$0.85$2.15
Output Tokens / Task
Tokens generated per task
45K58K
Reasoning Tokens / Task
Thinking tokens burned per task
22K32K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaCommand A PlusGPT-6 Astra
Official API Model ID (SDK)command-a-plusgpt-6-astra
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI Responses API & Chat Completions v1
Release Date2026-052026-09
Knowledge CutoffMarch 2026June 2026
ArchitectureFlagship Multimodal Agentic MoEOmni-Adaptive Autoregressive with Dynamic CoT
ParametersConfidential (~180B+ MoE)Confidential
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($3/1M in) across full 128K windowFlat rate ($10/1M in) across full 272K window
Prompt Cache Policy & TTLCached input at $0.75/1M tokensAutomatic prefix caching at $1/1M (no extra cache-write fee)
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 112 GB VRAM (4-bit Quantized) · 387 GB VRAM (Native BF16)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)OpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 ControlSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision, audio
Output Modalitiestexttext, audio

Command A Plus vs GPT-6 Astra: Respuestas Rápidas (FAQ)

Which is more intelligent, Command A Plus or GPT-6 Astra?

GPT-6 Astra is more intelligent. It scores 96 compared with 58 on the composite Intelligence Index.

Which model is faster?

GPT-6 Astra is faster, generating 100 tokens per second compared with 68 tokens per second.

Which model is cheaper to run?

Command A Plus is cheaper at $2.33 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Command A Plus has lower latency, with a time to first token of 0.56s compared with 0.95s.

Which model has a larger context window?

GPT-6 Astra has a larger context window, supporting 272K tokens compared with 128K tokens.

Veredicto

Tanto Command A Plus (Ideal para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, sistemas RAG empresariales y automatización mediante API.) como GPT-6 Astra (Ideal para síntesis de voz natural, transcripción acústica y procesamiento de audio en tiempo real, sistemas RAG empresariales y automatización mediante API.) destacan en producción: GPT-6 Astra lidera en inteligencia general y programación, GPT-6 Astra ofrece mayor velocidad de generación de tokens y Command A Plus resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, Command A Plus o GPT-6 Astra?+

En las pruebas de inteligencia compuesta y resolución de código, GPT-6 Astra obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de Command A Plus frente a GPT-6 Astra?+

Command A Plus cuesta $3.00 / $12.00 por millón de tokens de entrada/salida, mientras que GPT-6 Astra cuesta $10.00 / $50.00. En costo combinado, Command A Plus es la opción más económica.

¿Qué modelo tiene mayor ventana de contexto y menor latencia?+

Command A Plus cuenta con 128K tokens de contexto frente a 272K tokens de GPT-6 Astra. En velocidad de inferencia, GPT-6 Astra ofrece un rendimiento superior.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

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: Documentación oficial de API de Cohere y OpenAI, tarjetas de sistema y benchmarks independientes (2026).