Head-to-Head Model Comparison

Command A Vision vs Command A

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial

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Command A VisionProfile

Command AProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Cohere

Command A Vision

IA Multimodal Nativa

Command A Vision de Cohere es un modelo de IA diseñado para comprensión multimodal nativa de texto e imagen y análisis visual de documentos, con ventana de contexto de 128K, velocidad de 65 tokens/s, índice de inteligencia de 53/100 y tarif

Intelligence Index53 / 100

Input Token:

$2.50 / 1M

Output Token:

$10.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

45%

Cohere

Command A

IA Agéntica y Uso de Herramientas

Command A de Cohere es un modelo de IA diseñado para flujos de trabajo agénticos autónomos, llamada a herramientas y automatización compleja, con ventana de contexto de 256K, velocidad de 70 tokens/s, índice de inteligencia de 51/100 y tari

Intelligence Index51 / 100

Input Token:

$2.50 / 1M

Output Token:

$10.00 / 1M

Context Window:

256K tokens

SWE-bench Verified:

46%

Diferencias Clave de un Vistazo

Both models cost the same under this workload — choose on capability, not price.
Command A has a larger context window (256K vs 128K tokens).
Command A is faster at 70 tok/s vs 65 tok/s.
Command A leads on SWE-bench coding (46.0% vs 45.0%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Característica	Command A Vision	Command A
Intelligence Index Composite reasoning & knowledge score (0-100)	53	51
Provider	Cohere	Cohere
Input Price Cost per million input tokens	$2.50 / 1M	$2.50 / 1M
Output Price Cost per million output tokens	$10.00 / 1M	$10.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$2.02 / 1M	$2.02 / 1M
Context Window Maximum input + output tokens	128K tokens~192 A4 pages of text	256K tokens~384 A4 pages of text
Max Output Tokens Per single request	16K	16K
Throughput Speed Tokens generated per second	65 tok/s	70 tok/s
SWE-bench Verified Real-world software engineering	45%	46%
GPQA Diamond Graduate-level reasoning	62.5%	61%
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

+1.0% SWE-bench lead

Costo

Tied

Identical monthly runtime cost

Velocidad

Command A

+8% faster generation

Contexto

Command A

256K tokens window

Puntuaciones de Benchmarks Verificadas

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

Command A VisionCommand A

SWE-bench Verified (Autonomous Coding)

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

45%vs46%

GPQA Diamond (Doctorate-Level Science & Math)

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

62.5%vs61%

MMLU-Pro (Multi-task Language Understanding)

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

81.5%vs81%

LMSYS Chatbot Arena Elo

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

1345ptsvs1335pts

Terminal-Bench (Agentic Coding & Terminal Use)

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

41%vs42%

Long-Context Reasoning

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

83%vs84%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

65 tok/s vs70 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 Vision0.55s

Command A0.52s

Est. End-to-End Response (500 tokens)TTFT + generation time

Command A Vision8.24s

Command A7.66s

Simulador Interactivo de Costos de Tokens

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

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

Command A Vision Monthly API Bill

$13.88 / month

$2.5/1M in · $10/1M out

Command A Monthly API Bill

$13.88 / month

$2.5/1M in · $10/1M out

These models cost the same under this workload — no savings either way.Break-even

Command A Vision · Strengths & Key Advantages

Ventana de contexto de 128K con hasta 16K tokens de salida máxima (SWE-bench Verified 45% · GPQA Diamond 62.5%)
Rendimiento ágil de 65 tokens/segundo con latencia inicial (TTFT) de solo 550 ms
Pesos abiertos (Confidential (~110B+)) 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 · Strengths & Key Advantages

Ventana de contexto de 256K con hasta 16K tokens de salida máxima (SWE-bench Verified 46% · GPQA Diamond 61%)
Rendimiento ágil de 70 tokens/segundo con latencia inicial (TTFT) de solo 520 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.

Metric	Command A Vision	Command A
Cost per Task Estimated USD to finish one task	$0.80	$0.75
Output Tokens / Task Tokens generated per task	38K	38K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

Característica	Command A Vision	Command A
Official API Model ID (SDK)	command-a-vision	command-a
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2025-07	2025-03
Knowledge Cutoff	May 2025	January 2025
Architecture	Enterprise Multimodal Agent Transformer	Agentic Enterprise Transformer
Parameters	Confidential (~110B+)	Confidential (~100B+)
Enterprise Rate Limits (RPM / TPM)	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)	Flat rate ($2.5/1M in) across full 128K window	Flat rate ($2.5/1M in) across full 256K window
Prompt Cache Policy & TTL	Cached input at $0.75/1M tokens	Cached input at $0.75/1M tokens
Computer Use / GUI Agent	API / 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 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	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning Support	Full 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 Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)	Text BPE (~4 chars/token)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 68 GB VRAM (4-bit Quantized) · 237 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 Classification	Open-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 Control	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalities	text, vision	text
Output Modalities	text	text

Command A Vision vs Command A: Respuestas Rápidas (FAQ)

Which is more intelligent, Command A Vision or Command A?

Command A Vision is more intelligent. It scores 53 compared with 51 on the composite Intelligence Index.

Which model is faster?

Command A is faster, generating 70 tokens per second compared with 65 tokens per second.

Which model has lower latency?

Command A has lower latency, with a time to first token of 0.52s compared with 0.55s.

Which model has a larger context window?

Command A has a larger context window, supporting 256K tokens compared with 128K tokens.

Veredicto

Tanto Command A Vision (Ideal para comprensión multimodal nativa de texto e imagen y análisis visual de documentos, sistemas RAG empresariales y automatización mediante API.) como Command A (Ideal para flujos de trabajo agénticos autónomos, llamada a herramientas y automatización compleja, sistemas RAG empresariales y automatización mediante API.) destacan en producción: Command A Vision lidera en inteligencia general y programación, Command A ofrece mayor velocidad de generación de tokens y Command A Vision resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

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

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

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

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

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

Command A Vision cuenta con 128K tokens de contexto frente a 256K tokens de Command A. En velocidad de inferencia, Command A 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 & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Command A Vision vs Command A

Cambia y Compara Cualquier Modelo

Command A Vision

Command A

¿Quién gana en cada área?

Puntuaciones de Benchmarks Verificadas

Latencia y Tiempo de Respuesta

Simulador Interactivo de Costos de Tokens

Command A Vision · Strengths & Key Advantages

Considerations & Trade-offs

Command A · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificaciones Técnicas

Command A Vision vs Command A: Respuestas Rápidas (FAQ)

Veredicto

Preguntas frecuentes

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