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Head-to-Head Model Comparison

Command A Plus vs Gemini 4 Argon

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs araştırma ekibi tarafından incelendiSon inceleme: October 2026Yayın ilkeleri
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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

Cohere tarafından geliştirilen Command A Plus ve Google tarafından sunulan Gemini 4 Argon, kendi sınıflarının öne çıkan yapay zeka modelleridir. Command A Plus, 128K token bağlam penceresi ve 1M token başına $3.00/$12.00 fiyat sunarken; Gemini 4 Argon, 1M token bağlam penceresi ve $2.00/$10.00 fiyatla gelir. Aşağıda tüm benchmark, hız ve maliyet detaylarını inceleyebilirsiniz.

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Cohere

Command A Plus

Açık Ağırlıklı Temel Model

Cohere tarafından geliştirilen Command A Plus; özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği için tasarlanmış olup 128K bağlam penceresi, 68 token/sn hız, 58/100 zeka indeksi ve 1M token başına $3/$

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

Yerel Çok Modlu Yapay Zeka

Google tarafından geliştirilen Gemini 4 Argon; yerel çok modlu metin ve görsel anlama ile karmaşık belge analizi için tasarlanmış olup 1M bağlam penceresi, 115 token/sn hız, 97/100 zeka indeksi ve 1M token başına $2/$10 fiyatlandırma sunar.

Intelligence Index97 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

81.9%

Bir Bakışta Temel Farklar

  • 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

Hangi Alanda Kim Kazanıyor?

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

Doğrulanmış Benchmark Puanları

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

Gecikme Süresi ve Yanıt Hızı

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

Gerçek Zamanlı Token Maliyet Simülatörü

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

  • 128K bağlam penceresi ve yanıt başına maksimum 33K çıktı tokenı kapasitesi (SWE-bench Verified 60.5% · GPQA Diamond 74%)
  • Sadece 560 ms ilk token gecikmesi (TTFT) ile saniyede 68 token yüksek üretim hızı
  • vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (Confidential (~180B+ MoE))
Considerations & Trade-offs
  • Tam hassasiyette yerel GPU çıkarımı için yeterli VRAM kapasitesine sahip donanım altyapısı gerektirir
  • Yüksek hacimli üretim trafiğinde maliyetleri optimize etmek için Prompt Caching ve Batch API kullanımı önerilir

Gemini 4 Argon · Strengths & Key Advantages

  • 1M bağlam penceresi ve yanıt başına maksimum 1M çıktı tokenı kapasitesi (SWE-bench Verified 81.9% · GPQA Diamond 81.5%)
  • Sadece 850 ms ilk token gecikmesi (TTFT) ile saniyede 115 token yüksek üretim hızı
  • İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $2/$10 fiyatlandırma)
Considerations & Trade-offs
  • Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
  • Yüksek hacimli üretim trafiğinde maliyetleri optimize etmek için Prompt Caching ve Batch API kullanımı önerilir

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

Teknik Özellikler

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: Hızlı Yanıtlar (SSS)

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.

Sonuç

Hem Command A Plus (özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) hem de Gemini 4 Argon (yerel çok modlu metin ve görsel anlama ile karmaşık belge analizi, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: Gemini 4 Argon karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, Gemini 4 Argon daha yüksek üretim hızı sağlar; Gemini 4 Argon ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için Command A Plus mi yoksa Gemini 4 Argon mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde Gemini 4 Argon önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

Command A Plus ve Gemini 4 Argon API fiyatları nasıl karşılaştırılır?+

Command A Plus 1M giriş/çıkış tokeni başına $3.00 / $12.00 ücretlendirilirken, Gemini 4 Argon $2.00 / $10.00 seviyesindedir. Karma maliyette Gemini 4 Argon daha avantajlıdır.

Hangi modelin bağlam penceresi daha geniş ve hızı daha yüksek?+

Command A Plus 128K token bağlam penceresi sunarken Gemini 4 Argon 1M token kapasiteye sahiptir. Saniyedeki token üretim hızında ise Gemini 4 Argon öndedir.

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 & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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.

Resmi kaynaklar: Cohere ve Google resmi API dokümantasyonu, sistem kartları ve bağımsız benchmark testleri (2026).