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Head-to-Head Model Comparison

Command A Reasoning vs o3

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
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Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Command A Reasoning vs o3: Benchmarks, Pricing & Speed Comparison

Command A Reasoning de Cohere y o3 de OpenAI compiten directamente en el ecosistema actual de IA. Command A Reasoning ofrece una ventana de contexto de 256K tokens a $2.50/$10.00 por millón de tokens (entrada/salida), mientras que o3 ofrece 200K tokens de contexto a $2.00/$8.00 por millón de tokens. Analizamos sus benchmarks, latencia y costos reales.

Comparación Directa (VS)

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Cohere

Command A Reasoning

Razonamiento de Pesos Abiertos

Command A Reasoning de Cohere es un modelo de IA diseñado para razonamiento de cadena de pensamiento con pesos abiertos y alta eficiencia algorítmica, con ventana de contexto de 256K, velocidad de 55 tokens/s, índice de inteligencia de 55/1

Intelligence Index55 / 100
Input Token:

$2.50 / 1M

Output Token:

$10.00 / 1M

Context Window:

256K tokens

SWE-bench Verified:

53%

OpenAI

o3

Motor de Razonamiento Profundo

o3 de OpenAI es un modelo de IA diseñado para razonamiento lógico profundo, matemáticas avanzadas y resolución científica paso a paso, con ventana de contexto de 200K, velocidad de 75 tokens/s, índice de inteligencia de 56/100 y tarifa de $

Intelligence Index56 / 100
Input Token:

$2.00 / 1M

Output Token:

$8.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

69.1%

Diferencias Clave de un Vistazo

  • o3 is 1.3x cheaper for API usage (input + output tokens combined).
  • Command A Reasoning has a larger context window (256K vs 200K tokens).
  • o3 is faster at 75 tok/s vs 55 tok/s.
  • o3 leads on SWE-bench coding (69.1% vs 53.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaCommand A Reasoningo3
Intelligence Index
Composite reasoning & knowledge score (0-100)
5556
Provider
CohereOpenAI
Input Price
Cost per million input tokens
$2.50 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$10.00 / 1M$8.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$2.02 / 1M$1.55 / 1M
Context Window
Maximum input + output tokens
256K tokens~384 A4 pages of text200K tokens~300 A4 pages of text
Max Output Tokens
Per single request
33K100K
Throughput Speed
Tokens generated per second
55 tok/s75 tok/s
SWE-bench Verified
Real-world software engineering
53%69.1%
GPQA Diamond
Graduate-level reasoning
70%76.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.75 / 1M$0.50 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
o3
+16.1% SWE-bench lead
Costo
o3
1.3x cheaper monthly runtime
Velocidad
o3
+36% faster generation
Contexto
Command A Reasoning
256K tokens window

Puntuaciones de Benchmarks Verificadas

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

Command A Reasoningo3
SWE-bench Verified (Autonomous Coding)

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

53%vs69.1%
GPQA Diamond (Doctorate-Level Science & Math)

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

70%vs76.5%
MMLU-Pro (Multi-task Language Understanding)

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

84.5%vs87%
LMSYS Chatbot Arena Elo

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

1370ptsvs1345pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs12.9%
Terminal-Bench (Agentic Coding & Terminal Use)

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

47%vs42%
SciCode (Scientific Computing)

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

N/Avs42.5%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs70.5%
AIME (Advanced Math Competition)

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

78%vs91.6%
Long-Context Reasoning

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

86%vs78.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

55 tok/s vs75 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 Reasoning0.75s
o32.80s
Est. End-to-End Response (500 tokens)TTFT + generation time
Command A Reasoning9.84s
o39.47s

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 Reasoning Monthly API Bill
$13.88 / month
$2.5/1M in · $10/1M out
o3 Monthly API Bill
$10.95 / month
$2/1M in · $8/1M out
o3 saves approximately $2.93 / month (21%) under this workload.1.3x Savings

Command A Reasoning · Strengths & Key Advantages

  • Ventana de contexto de 256K con hasta 33K tokens de salida máxima (SWE-bench Verified 53% · GPQA Diamond 70%)
  • Rendimiento ágil de 55 tokens/segundo con latencia inicial (TTFT) de solo 750 ms
  • Pesos abiertos (Confidential (~100B+)) 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

o3 · Strengths & Key Advantages

  • Ventana de contexto de 200K con hasta 100K tokens de salida máxima (SWE-bench Verified 69.1% · GPQA Diamond 76.5%)
  • Rendimiento ágil de 75 tokens/segundo con latencia inicial (TTFT) de solo 2800 ms
  • Economía de API competitiva ($2/$8 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 Reasoningo3
Cost per Task
Estimated USD to finish one task
$0.95$1.35
Output Tokens / Task
Tokens generated per task
45K48K
Reasoning Tokens / Task
Thinking tokens burned per task
22K26K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaCommand A Reasoningo3
Official API Model ID (SDK)command-a-reasoningo3
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI Responses API & Chat Completions v1
Release Date2025-082025-04
Knowledge CutoffJune 2025June 2024
ArchitectureEnterprise Chain-of-Thought Reasoning TransformerReasoning transformer with adjustable thinking effort
ParametersConfidential (~100B+)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 ($2.5/1M in) across full 256K windowFlat rate ($2/1M in) across full 200K window
Prompt Cache Policy & TTLCached input at $0.75/1M tokensAutomatic prefix caching at $0.5/1M (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)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 62 GB VRAM (4-bit Quantized) · 215 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 Modalitiestexttext, vision
Output Modalitiestexttext

Command A Reasoning vs o3: Respuestas Rápidas (FAQ)

Which is more intelligent, Command A Reasoning or o3?

o3 is more intelligent. It scores 56 compared with 55 on the composite Intelligence Index.

Which model is faster?

o3 is faster, generating 75 tokens per second compared with 55 tokens per second.

Which model is cheaper to run?

o3 is cheaper at $1.55 per 1M tokens blended, compared with $2.02 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Command A Reasoning has lower latency, with a time to first token of 0.75s compared with 2.80s.

Which model has a larger context window?

Command A Reasoning has a larger context window, supporting 256K tokens compared with 200K tokens.

Veredicto

Tanto Command A Reasoning (Ideal para razonamiento de cadena de pensamiento con pesos abiertos y alta eficiencia algorítmica, sistemas RAG empresariales y automatización mediante API.) como o3 (Ideal para razonamiento lógico profundo, matemáticas avanzadas y resolución científica paso a paso, sistemas RAG empresariales y automatización mediante API.) destacan en producción: o3 lidera en inteligencia general y programación, o3 ofrece mayor velocidad de generación de tokens y o3 resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, Command A Reasoning o o3?+

En las pruebas de inteligencia compuesta y resolución de código, o3 obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de Command A Reasoning frente a o3?+

Command A Reasoning cuesta $2.50 / $10.00 por millón de tokens de entrada/salida, mientras que o3 cuesta $2.00 / $8.00. En costo combinado, o3 es la opción más económica.

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

Command A Reasoning cuenta con 256K tokens de contexto frente a 200K tokens de o3. En velocidad de inferencia, o3 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.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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).