Head-to-Head Model Comparison

Command A Vision vs Command A

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: 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

O Command A Vision da Cohere é um modelo de IA projetado para compreensão multimodal nativa de texto e imagem e leitura visual de documentos, oferecendo janela de contexto de 128K, velocidade de 65 tokens/s, índice de inteligência de 53/100

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 Agêntica e Uso de Ferramentas

O Command A da Cohere é um modelo de IA projetado para fluxos de trabalho agênticos autônomos, chamada de ferramentas e automação, oferecendo janela de contexto de 256K, velocidade de 70 tokens/s, índice de inteligência de 51/100 e tarifa d

Intelligence Index51 / 100

Input Token:

$2.50 / 1M

Output Token:

$10.00 / 1M

Context Window:

256K tokens

SWE-bench Verified:

46%

Principais Diferenças em Resumo

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 →

Feature	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

Quem vence em cada categoria?

At-a-glance decision framework

Coding

Command A

+1.0% SWE-bench lead

Cost

Tied

Identical monthly runtime cost

Speed

Command A

+8% faster generation

Context

Command A

256K tokens window

Pontuações 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

Latência e Tempo de Resposta

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 Interativo de Custo 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

Janela de contexto de 128K com limite máximo de saída de 16K tokens (SWE-bench Verified 45% · GPQA Diamond 62.5%)
Taxa de transferência rápida de 65 tokens/segundo com latência inicial (TTFT) de 550 ms
Pesos abertos (Confidential (~110B+)) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama

Considerations & Trade-offs

Requer servidores GPU com memória VRAM adequada para execução local em precisão total
Para alto volume de requisições, recomenda-se ativar o cache de prompts e a Batch API para reduzir custos

Command A · Strengths & Key Advantages

Janela de contexto de 256K com limite máximo de saída de 16K tokens (SWE-bench Verified 46% · GPQA Diamond 61%)
Taxa de transferência rápida de 70 tokens/segundo com latência inicial (TTFT) de 520 ms
Pesos abertos (Confidential (~100B+)) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama

Considerations & Trade-offs

Requer servidores GPU com memória VRAM adequada para execução local em precisão total
Para alto volume de requisições, recomenda-se ativar o cache de prompts e a Batch API para reduzir custos

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

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

Feature	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: Respostas 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.

Veredito

Tanto Command A Vision (Indicado para compreensão multimodal nativa de texto e imagem e leitura visual de documentos, arquiteturas RAG corporativas e integração escalável via API.) quanto Command A (Indicado para fluxos de trabalho agênticos autônomos, chamada de ferramentas e automação, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Command A Vision lidera em inteligência geral e programação, Command A oferece geração mais rápida e Command A Vision apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Command A Vision ou Command A?+

Nas avaliações de inteligência e código, Command A Vision leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Command A Vision ou Command A?+

O Command A Vision custa $2.50 / $10.00 por 1M de tokens (entrada/saída) e o Command A custa $2.50 / $10.00. No custo combinado, Command A Vision é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Command A Vision suporta 128K tokens de contexto contra 256K tokens do Command A, enquanto Command A entrega maior velocidade de geração.

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

Troque e Compare Qualquer Modelo

Command A Vision

Command A

Quem vence em cada categoria?

Pontuações de Benchmarks Verificadas

Latência e Tempo de Resposta

Simulador Interativo de Custo de Tokens

Command A Vision · Strengths & Key Advantages

Considerations & Trade-offs

Command A · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificações Técnicas

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

Veredito

Perguntas Frequentes (FAQ)

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