Head-to-Head Model Comparison

Command A Plus vs Command A Reasoning

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 Plus vs Command A Reasoning: Benchmarks, Pricing & Speed Comparison

Command A Plus de Cohere y Command A Reasoning de Cohere 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 Command A Reasoning ofrece 256K tokens de contexto a $2.50/$10.00 por millón de tokens. Analizamos sus benchmarks, latencia y costos reales.

Comparación Directa (VS)

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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%

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%

Diferencias Clave de un Vistazo

  • Command A Reasoning is 1.2x cheaper for API usage (input + output tokens combined).
  • Command A Reasoning has a larger context window (256K vs 128K tokens).
  • Command A Plus is faster at 68 tok/s vs 55 tok/s.
  • Command A Plus leads on SWE-bench coding (60.5% vs 53.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaCommand A PlusCommand A Reasoning
Intelligence Index
Composite reasoning & knowledge score (0-100)
5855
Provider
CohereCohere
Input Price
Cost per million input tokens
$3.00 / 1M$2.50 / 1M
Output Price
Cost per million output tokens
$12.00 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$2.33 / 1M$2.02 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text256K tokens~384 A4 pages of text
Max Output Tokens
Per single request
33K33K
Throughput Speed
Tokens generated per second
68 tok/s55 tok/s
SWE-bench Verified
Real-world software engineering
60.5%53%
GPQA Diamond
Graduate-level reasoning
74%70%
Cached Input Price
Prompt caching discount per 1M tokens
$0.75 / 1M$0.75 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
Command A Plus
+7.5% SWE-bench lead
Costo
Command A Reasoning
1.2x cheaper monthly runtime
Velocidad
Command A Plus
+24% 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 PlusCommand A Reasoning
SWE-bench Verified (Autonomous Coding)

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

60.5%vs53%
GPQA Diamond (Doctorate-Level Science & Math)

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

74%vs70%
MMLU-Pro (Multi-task Language Understanding)

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

86.8%vs84.5%
LMSYS Chatbot Arena Elo

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

1410ptsvs1370pts
Terminal-Bench (Agentic Coding & Terminal Use)

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

50%vs47%
AIME (Advanced Math Competition)

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

82.5%vs78%
Long-Context Reasoning

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

88%vs86%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

68 tok/s vs55 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
Command A Reasoning0.75s
Est. End-to-End Response (500 tokens)TTFT + generation time
Command A Plus7.91s
Command A Reasoning9.84s

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
Command A Reasoning Monthly API Bill
$13.88 / month
$2.5/1M in · $10/1M out
Command A Reasoning saves approximately $2.55 / month (16%) under this workload.1.2x 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

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

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricCommand A PlusCommand A Reasoning
Cost per Task
Estimated USD to finish one task
$0.85$0.95
Output Tokens / Task
Tokens generated per task
45K45K
Reasoning Tokens / Task
Thinking tokens burned per task
22K22K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaCommand A PlusCommand A Reasoning
Official API Model ID (SDK)command-a-pluscommand-a-reasoning
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2026-052025-08
Knowledge CutoffMarch 2026June 2025
ArchitectureFlagship Multimodal Agentic MoEEnterprise Chain-of-Thought Reasoning Transformer
ParametersConfidential (~180B+ MoE)Confidential (~100B+)
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed CloudUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Flat rate ($3/1M in) across full 128K windowFlat rate ($2.5/1M in) across full 256K window
Prompt Cache Policy & TTLCached input at $0.75/1M tokensCached input at $0.75/1M tokens
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
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 toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token)
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)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 62 GB VRAM (4-bit Quantized) · 215 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestext, visiontext
Output Modalitiestexttext

Command A Plus vs Command A Reasoning: Respuestas Rápidas (FAQ)

Which is more intelligent, Command A Plus or Command A Reasoning?

Command A Plus is more intelligent. It scores 58 compared with 55 on the composite Intelligence Index.

Which model is faster?

Command A Plus is faster, generating 68 tokens per second compared with 55 tokens per second.

Which model is cheaper to run?

Command A Reasoning is cheaper at $2.02 per 1M tokens blended, compared with $2.33 (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 0.75s.

Which model has a larger context window?

Command A Reasoning has a larger context window, supporting 256K 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 Command A Reasoning (Ideal para razonamiento de cadena de pensamiento con pesos abiertos y alta eficiencia algorítmica, sistemas RAG empresariales y automatización mediante API.) destacan en producción: Command A Plus lidera en inteligencia general y programación, Command A Plus ofrece mayor velocidad de generación de tokens y Command A Reasoning resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

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

En las pruebas de inteligencia compuesta y resolución de código, Command A Plus 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 Command A Reasoning?+

Command A Plus cuesta $3.00 / $12.00 por millón de tokens de entrada/salida, mientras que Command A Reasoning cuesta $2.50 / $10.00. En costo combinado, Command A Reasoning 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 256K tokens de Command A Reasoning. En velocidad de inferencia, Command A Plus 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 Cohere, tarjetas de sistema y benchmarks independientes (2026).