Head-to-Head Model Comparison

Command A Plus vs Gemini 4 Argon

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Command A Plus vs Gemini 4 Argon: Benchmarks, Pricing & Speed Comparison

Command A Plus da Cohere e Gemini 4 Argon da Google são dois modelos de IA de destaque. O Command A Plus oferece uma janela de contexto de 128K tokens a $3.00/$12.00 por milhão de tokens, enquanto o Gemini 4 Argon oferece 1M tokens de contexto a $2.00/$10.00 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.

Comparação Direta (VS)

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Cohere

Command A Plus

Modelo Base de Pesos Abertos

O Command A Plus da Cohere é um modelo de IA projetado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, oferecendo janela de contexto de 128K, velocidade de 68 tokens/s, índice de inteligência de 58/100 e ta

Intelligence Index58 / 100
Input Token:

$3.00 / 1M

Output Token:

$12.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

60.5%

Google

Gemini 4 Argon

IA Multimodal Nativa

O Gemini 4 Argon da Google é um modelo de IA projetado para compreensão multimodal nativa de texto e imagem e leitura visual de documentos, oferecendo janela de contexto de 1M, velocidade de 115 tokens/s, índice de inteligência de 97/100 e

Intelligence Index97 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

81.9%

Principais Diferenças em Resumo

  • Gemini 4 Argon is 1.4x cheaper for API usage (input + output tokens combined).
  • Gemini 4 Argon has a larger context window (1M vs 128K tokens).
  • Gemini 4 Argon is faster at 115 tok/s vs 68 tok/s.
  • Gemini 4 Argon leads on SWE-bench coding (81.9% vs 60.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureCommand A PlusGemini 4 Argon
Intelligence Index
Composite reasoning & knowledge score (0-100)
5897
Provider
CohereGoogle
Input Price
Cost per million input tokens
$3.00 / 1M$2.00 / 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$1.47 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
33K1000K
Throughput Speed
Tokens generated per second
68 tok/s115 tok/s
SWE-bench Verified
Real-world software engineering
60.5%81.9%
GPQA Diamond
Graduate-level reasoning
74%81.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.75 / 1M$0.10 / 1M

Quem vence em cada categoria?

At-a-glance decision framework
Coding
Gemini 4 Argon
+21.4% SWE-bench lead
Cost
Gemini 4 Argon
1.4x cheaper monthly runtime
Speed
Gemini 4 Argon
+69% faster generation
Context
Gemini 4 Argon
1M tokens window

Pontuações de Benchmarks Verificadas

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

Command A PlusGemini 4 Argon
SWE-bench Verified (Autonomous Coding)

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

60.5%vs81.9%
GPQA Diamond (Doctorate-Level Science & Math)

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

74%vs81.5%
MMLU-Pro (Multi-task Language Understanding)

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

86.8%vs90.8%
LMSYS Chatbot Arena Elo

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

1410ptsvs1525pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs18.9%
Terminal-Bench (Agentic Coding & Terminal Use)

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

50%vs57.4%
SciCode (Scientific Computing)

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

N/Avs56.4%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs80.5%
AIME (Advanced Math Competition)

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

82.5%vs94.8%
Long-Context Reasoning

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

88%vs96.4%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

68 tok/s vs115 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 Plus0.56s
Gemini 4 Argon0.85s
Est. End-to-End Response (500 tokens)TTFT + generation time
Command A Plus7.91s
Gemini 4 Argon5.20s

Simulador Interativo de Custo 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
Gemini 4 Argon Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Gemini 4 Argon saves approximately $4.28 / month (26%) under this workload.1.4x Savings

Command A Plus · Strengths & Key Advantages

  • Janela de contexto de 128K com limite máximo de saída de 33K tokens (SWE-bench Verified 60.5% · GPQA Diamond 74%)
  • Taxa de transferência rápida de 68 tokens/segundo com latência inicial (TTFT) de 560 ms
  • Pesos abertos (Confidential (~180B+ MoE)) 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

Gemini 4 Argon · Strengths & Key Advantages

  • Janela de contexto de 1M com limite máximo de saída de 1M tokens (SWE-bench Verified 81.9% · GPQA Diamond 81.5%)
  • Taxa de transferência rápida de 115 tokens/segundo com latência inicial (TTFT) de 850 ms
  • Economia de API competitiva ($2/$10 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
  • Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
  • 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.

MetricCommand A PlusGemini 4 Argon
Cost per Task
Estimated USD to finish one task
$0.85$2.45
Output Tokens / Task
Tokens generated per task
45K75K
Reasoning Tokens / Task
Thinking tokens burned per task
22K36K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

FeatureCommand A PlusGemini 4 Argon
Official API Model ID (SDK)command-a-plusmodels/gemini-4-argon
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIGoogle Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2026-052026-09
Knowledge CutoffMarch 2026June 2026
ArchitectureFlagship Multimodal Agentic MoEPathways Multimodal Sparse Mixture-of-Experts
ParametersConfidential (~180B+ MoE)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) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($3/1M in) across full 128K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.75/1M tokensImplicit + Explicit Context Caching at $0.1/1M with configurable TTL
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 toolsBuilt-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Vertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)
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)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)Google DeepMind Frontier Safety Framework Verified
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 Modalitiestext, visiontext, vision, audio, video
Output Modalitiestexttext

Command A Plus vs Gemini 4 Argon: Respostas Rápidas (FAQ)

Which is more intelligent, Command A Plus or Gemini 4 Argon?

Gemini 4 Argon is more intelligent. It scores 97 compared with 58 on the composite Intelligence Index.

Which model is faster?

Gemini 4 Argon is faster, generating 115 tokens per second compared with 68 tokens per second.

Which model is cheaper to run?

Gemini 4 Argon is cheaper at $1.47 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 0.85s.

Which model has a larger context window?

Gemini 4 Argon has a larger context window, supporting 1M tokens compared with 128K tokens.

Veredito

Tanto Command A Plus (Indicado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, arquiteturas RAG corporativas e integração escalável via API.) quanto Gemini 4 Argon (Indicado para compreensão multimodal nativa de texto e imagem e leitura visual de documentos, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Gemini 4 Argon lidera em inteligência geral e programação, Gemini 4 Argon oferece geração mais rápida e Gemini 4 Argon apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Command A Plus ou Gemini 4 Argon?+

Nas avaliações de inteligência e código, Gemini 4 Argon leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Command A Plus ou Gemini 4 Argon?+

O Command A Plus custa $3.00 / $12.00 por 1M de tokens (entrada/saída) e o Gemini 4 Argon custa $2.00 / $10.00. No custo combinado, Gemini 4 Argon é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Command A Plus suporta 128K tokens de contexto contra 1M tokens do Gemini 4 Argon, enquanto Gemini 4 Argon 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.

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Fontes oficiais: Documentação oficial de API da Cohere e Google e benchmarks independentes (2026).