Head-to-Head Model Comparison

Command A Plus 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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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: Benchmarks, Pricing & Speed Comparison

Command A Plus by Cohere and Command A by Cohere represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Command A holds a notable pricing advantage for token ingestion. On output generation, Command A is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Command A provides an expanded memory horizon with 256K tokens. In latency-sensitive production environments, Command A leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.

Comparación Directa (VS)

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Cohere

Command A Plus

Comando más fuerte

de Cohere líder 2026 multimodal insignia motor uniting visual documento razonamiento, profundo cadena de pensamiento, y soberano empresarial implementación.

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

Agente empresarial

comercial insignia agente modelo con 256K contexto, hardened multipaso herramienta ejecución, y soberano implementación soporte.

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

  • Command A is 1.2x cheaper for API usage (input + output tokens combined).
  • Command A has a larger context window (256K vs 128K tokens).
  • Command A is faster at 70 tok/s vs 68 tok/s.
  • Command A Plus leads on SWE-bench coding (60.5% vs 46.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaCommand A PlusCommand A
Intelligence Index
Composite reasoning & knowledge score (0-100)
5851
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
33K16K
Throughput Speed
Tokens generated per second
68 tok/s70 tok/s
SWE-bench Verified
Real-world software engineering
60.5%46%
GPQA Diamond
Graduate-level reasoning
74%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 Plus
+14.5% SWE-bench lead
Costo
Command A
1.2x cheaper monthly runtime
Velocidad
Command A
+3% faster generation
Contexto
Command A
256K tokens window

Puntuaciones de Benchmarks Verificadas

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

Command A PlusCommand A
SWE-bench Verified (Autonomous Coding)

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

60.5%vs46%
GPQA Diamond (Doctorate-Level Science & Math)

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

74%vs61%
MMLU-Pro (Multi-task Language Understanding)

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

86.8%vs81%
LMSYS Chatbot Arena Elo

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

1410ptsvs1335pts
Terminal-Bench (Agentic Coding & Terminal Use)

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

50%vs42%
AIME (Advanced Math Competition)

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

82.5%vsN/A
Long-Context Reasoning

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

88%vs84%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

68 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 Plus0.56s
Command A0.52s
Est. End-to-End Response (500 tokens)TTFT + generation time
Command A Plus7.91s
Command A7.66s

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

Command A Plus · Strengths & Key Advantages

  • de Cohere la mayoría de potente modelo fundacional un date, blending visión, razonamiento, y agentes
  • Flawless recuperación fundamentación con strict anti-hallucination citas verificación
  • de pesos abiertos availability para soberano national y regulated empresarial implementaciones
Considerations & Trade-offs
  • Premium API token precios ($3.00/$12.00)
  • alto hardware requirements para local clúster alojamiento propio

Command A · Strengths & Key Advantages

  • Engineered specifically para autónomo empresarial agentes y confiable multi-herramienta chaining
  • Expansive 256K ventana de contexto con alto needle-en-un-haystack retention
  • empresarial-grade privacy guarantees con en-premise implementación options
Considerations & Trade-offs
  • Premium precios ($2.50/$10.00) en comparación con económico commodity modelos
  • texto-solo sin nativo imagen visión features

Token Use & Task Economics

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

MetricCommand A PlusCommand A
Cost per Task
Estimated USD to finish one task
$0.85$0.75
Output Tokens / Task
Tokens generated per task
45K38K
Reasoning Tokens / Task
Thinking tokens burned per task
22K0K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaCommand A PlusCommand A
Official API Model ID (SDK)command-a-pluscommand-a
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2026-052025-03
Knowledge CutoffMarch 2026January 2025
ArchitectureFlagship Multimodal Agentic MoEAgentic Enterprise 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: Respuestas Rápidas (FAQ)

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

Command A Plus is more intelligent. It scores 58 compared with 51 on the composite Intelligence Index.

Which model is faster?

Command A is faster, generating 70 tokens per second compared with 68 tokens per second.

Which model is cheaper to run?

Command A 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 has lower latency, with a time to first token of 0.52s compared with 0.56s.

Which model has a larger context window?

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

Veredicto

Verdict & Model Selection Recommendation: Choose Command A Plus if your priority is Enterprise intelligence platforms, sovereign government automation, and mission-critical agent workflows. Its performance in demanding tasks justifies its operational token cost. Choose Command A if your workflow prioritizes Enterprise autonomous agents, multi-step ERP workflows, and secure corporate automation. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

Preguntas frecuentes

How does Command A Plus compare to Command A in API token pricing and cost per token?+

Command A Plus costs $3.00 per 1M input tokens and $12.00 per 1M output tokens, whereas Command A costs $2.50 input and $10.00 output. Overall, Command A is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.

Which model has a larger context window: Command A Plus or Command A?+

Command A Plus supports a context window of 128K tokens (~96k words), while Command A supports 256K tokens (~192k words). Therefore, Command A can process more textual data and document context in a single prompt.

Which AI model is better for software engineering and coding: Command A Plus or Command A?+

Command A Plus scores 60.5% on SWE-bench Verified while Command A scores 46%. For autonomous software engineering and multi-file debugging, Command A Plus holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Command A Plus and Command A?+

Command A Plus features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Command A focuses on standard fast inference.

How does inference speed (tokens per second) compare between Command A Plus and Command A?+

Command A Plus generates approximately 68 tokens per second, while Command A delivers 70 tokens per second. In latency-sensitive production environments, Command A provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining Command A Plus and Command A to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Command A to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Command A Plus. This tiered routing pattern cuts overall API bills by up to 70%.

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: GetInfoUs Independent AI Benchmarks & Official API Specs