Head-to-Head Model Comparison

Grok 4.1 vs Gemini 4 Argon

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Vérifié par l’équipe de recherche de GetInfoUsDernière révision : October 2026Politique éditoriale
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Compare Grok 4.1 by xAI against Gemini 4 Argon by Google across real-world coding, reasoning, token economics, and latency.

Comparaison Face-à-Face (VS)

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xAI

Grok 4.1

Disrupteur économique

de xAI économique disruptor pairing un massif 2M-token contexte avec ultra-faible $0.20/1M tarification et un 3x inférieur hallucination rate que Grok 4.0 — conçu pour élevé-volume charges de travail.

Intelligence Index51 / 100
Input Token:

$0.20 / 1M

Output Token:

$1.00 / 1M

Context Window:

2M tokens

SWE-bench Verified:

66.4%

Google

Gemini 4 Argon

Roi multimodal avec sortie 1M

Google de DeepMind phare de pointe raisonnement moteur intégrant 1-millions-token sortie limits, autonome cybersecurity defense, et en temps réel audio/vision ingestion.

Intelligence Index97 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

81.9%

Différences Clés en un Coup d’Œil

  • Grok 4.1 is 9.5x cheaper for API usage (input + output tokens combined).
  • Grok 4.1 has a larger context window (2M vs 1M tokens).
  • Grok 4.1 is faster at 142 tok/s vs 115 tok/s.
  • Gemini 4 Argon leads on SWE-bench coding (81.9% vs 66.4%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaractéristiqueGrok 4.1Gemini 4 Argon
Intelligence Index
Composite reasoning & knowledge score (0-100)
5197
Provider
xAIGoogle
Input Price
Cost per million input tokens
$0.20 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$1.00 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.17 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
2M tokens~3,000 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
66K1000K
Throughput Speed
Tokens generated per second
142 tok/s115 tok/s
SWE-bench Verified
Real-world software engineering
66.4%81.9%
GPQA Diamond
Graduate-level reasoning
63.8%81.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.05 / 1M$0.10 / 1M

Qui gagne où ?

At-a-glance decision framework
Code
Gemini 4 Argon
+15.5% SWE-bench lead
Coût
Grok 4.1
9.5x cheaper monthly runtime
Vitesse
Grok 4.1
+23% faster generation
Contexte
Grok 4.1
2M tokens window

Scores de Benchmarks Vérifiés

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

Grok 4.1Gemini 4 Argon
SWE-bench Verified (Autonomous Coding)

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

66.4%vs81.9%
GPQA Diamond (Doctorate-Level Science & Math)

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

63.8%vs81.5%
MMLU-Pro (Multi-task Language Understanding)

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

80.1%vs90.8%
LMSYS Chatbot Arena Elo

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

1298ptsvs1525pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

8.2%vs18.9%
Terminal-Bench (Agentic Coding & Terminal Use)

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

38.5%vs57.4%
SciCode (Scientific Computing)

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

37.4%vs56.4%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

64.9%vs80.5%
AIME (Advanced Math Competition)

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

79.3%vs94.8%
Long-Context Reasoning

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

76.2%vs96.4%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

142 tok/s vs115 tok/s

Latence et Temps de Réponse

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
Grok 4.11.50s
Gemini 4 Argon0.85s
Est. End-to-End Response (500 tokens)TTFT + generation time
Grok 4.15.02s
Gemini 4 Argon5.20s

Simulateur Interactif de Coût 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)
Grok 4.1 Monthly API Bill
$1.28 / month
$0.2/1M in · $1/1M out
Gemini 4 Argon Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Grok 4.1 saves approximately $10.88 / month (90%) under this workload.9.5x Savings

Grok 4.1 · Strengths & Key Advantages

  • ultra-faible tarification — up à 25x cheaper que premium flagships
  • massif 2M-token fenêtre de contexte
  • 3x inférieur hallucination rate que Grok 4.0
  • le plus élevé débit dans classe (142 tok/s)
Considerations & Trade-offs
  • inférieur sommet raisonnement et codage que haut de gamme-3 flagships
  • Smaller écosystème et tooling que OpenAI / Anthropic

Gemini 4 Argon · Strengths & Key Advantages

  • Groundbreaking 1,000,000 token maximum sortie génération capacité via long Decode Continuation
  • 1M-token entrée window avec 99.7% GraphWalks recall (84.2% dans le 256K-1M range)
  • natif traitement de complet audio, vidéo streams, et visuel données (91.7% sur LVBench)
  • Half le token prix de d'Anthropic Opus 5.5 et #1 sur Chatbot Arena (1525 Elo)
Considerations & Trade-offs
  • massif token outputs peut incur élevé absolute coûts if unconstrained (~62K sortie tokens par index tâche)
  • $2/$10 tarification est un introductory 50% discount; standard rates revert à $4/$20 once le promotion ends

Token Use & Task Economics

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

MetricGrok 4.1Gemini 4 Argon
Cost per Task
Estimated USD to finish one task
$0.28$2.45
Output Tokens / Task
Tokens generated per task
40K75K
Reasoning Tokens / Task
Thinking tokens burned per task
21K36K

Spécifications Techniques

Architecture, release timeline, capabilities, and modalities.

CaractéristiqueGrok 4.1Gemini 4 Argon
Official API Model ID (SDK)grok-4-1-latestmodels/gemini-4-argon
API ProtocolxAI REST API (OpenAI-Compatible)Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2025-112026-09
Knowledge Cutoff2025June 2026
ArchitectureSparse MoEPathways Multimodal Sparse Mixture-of-Experts
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.2/1M in) across full 2000K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.05/1M 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 & SandboxReal-time Web & X (Twitter) Search Grounding + Code ExecutionBuilt-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationVertex 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 VRAMCloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationxAI Production Safety & Alignment VerifiedGoogle DeepMind Frontier Safety Framework Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision, audio, video
Output Modalitiestexttext

Grok 4.1 vs Gemini 4 Argon: Réponses Rapides (FAQ)

Which is more intelligent, Grok 4.1 or Gemini 4 Argon?

Gemini 4 Argon is more intelligent. It scores 97 compared with 51 on the composite Intelligence Index.

Which model is faster?

Grok 4.1 is faster, generating 142 tokens per second compared with 115 tokens per second.

Which model is cheaper to run?

Grok 4.1 is cheaper at $0.17 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 4 Argon has lower latency, with a time to first token of 0.85s compared with 1.50s.

Which model has a larger context window?

Grok 4.1 has a larger context window, supporting 2M tokens compared with 1M tokens.

Verdict

Choose Grok 4.1 for élevé-volume applications, économique-constrained projects, données extraction, et grand-échelle prototyping, or choose Gemini 4 Argon for whole-dépôt génération de code, complet-book synthèse, vidéo compréhension, et multi-hour audio traitement.

Questions fréquentes

Which is cheaper: Grok 4.1 or Gemini 4 Argon?+

Grok 4.1 costs $0.2/1M input and $1/1M output tokens, while Gemini 4 Argon costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: Grok 4.1 or Gemini 4 Argon?+

Grok 4.1 supports 2M tokens whereas Gemini 4 Argon supports 1M tokens.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.

Sources: xAI & Google Official Documentation