Grok-4 vs Gemini 4 Argon
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Grok-4 by xAI and Gemini 4 Argon by Google 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, Gemini 4 Argon holds a notable pricing advantage for token ingestion. On output generation, costs are matched. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 1,000K tokens. In latency-sensitive production environments, Grok-4 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.
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Grok-4
Real-Time Frontier ColossusxAI's frontier multimodal reasoning system trained on the 100k+ H100/H200 Colossus cluster with native zero-latency X stream indexing.
$2.50 / 1M
$10.00 / 1M
1M tokens
76.5%
Gemini 4 Argon
1M Output Multimodal KingGoogle DeepMind's flagship frontier reasoning engine featuring 1-million-token output limits, autonomous cybersecurity defense, and real-time audio/vision ingestion.
$2.00 / 1M
$10.00 / 1M
1M tokens
81.9%
Key Differences at a Glance
- Gemini 4 Argon is 1.1x cheaper for API usage (input + output tokens combined).
- Grok-4 is faster at 125 tok/s vs 115 tok/s.
- Gemini 4 Argon leads on SWE-bench coding (81.9% vs 76.5%).
| Feature | Grok-4 | Gemini 4 Argon |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 92 | 97 |
Provider | xAI | |
Input Price Cost per million input tokens | $2.50 / 1M | $2.00 / 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 | $1.68 / 1M | $1.47 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 64K | 1000K |
Throughput Speed Tokens generated per second | 125 tok/s | 115 tok/s |
SWE-bench Verified Real-world software engineering | 76.5% | 81.9% |
GPQA Diamond Graduate-level reasoning | 77.8% | 81.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.25 / 1M | $0.10 / 1M |
Who Wins Where?
At-a-glance decision frameworkEmpirical Head-to-Head Benchmark Scores
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latency & Response Time
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Real-Time Interactive Token Cost Simulator
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Grok-4 · Strengths & Key Advantages
- Zero-day knowledge synthesis via direct live X feed integration
- Ultra-low latency inference and high output throughput (125 tps)
- Uninhibited conversational tone with reduced corporate guardrail refusal
- Exceptional competitive math and coding performance
Considerations & Trade-offs
- Context retrieval over 800K tokens has minor edge-case variance
- Less specialized in niche enterprise legal documentation than Claude Opus
Gemini 4 Argon · Strengths & Key Advantages
- Groundbreaking 1,000,000 token maximum output generation capacity via Long Decode Continuation
- 1M-token input window with 99.7% GraphWalks recall (84.2% in the 256K-1M range)
- Native processing of full audio, video streams, and visual data (91.7% on LVBench)
- Half the token price of Anthropic's Opus 5.5 and #1 on Chatbot Arena (1525 Elo)
Considerations & Trade-offs
- Massive token outputs can incur high absolute costs if unconstrained (~62K output tokens per index task)
- $2/$10 pricing is an introductory 50% discount; standard rates revert to $4/$20 once the promotion ends
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Grok-4 | Gemini 4 Argon |
|---|---|---|
Cost per Task Estimated USD to finish one task | $1.65 | $2.45 |
Output Tokens / Task Tokens generated per task | 48K | 75K |
Reasoning Tokens / Task Thinking tokens burned per task | 24K | 36K |
Technical Specifications
Architecture, release timeline, capabilities, and modalities.
| Feature | Grok-4 | Gemini 4 Argon |
|---|---|---|
| Official API Model ID (SDK) | grok-4-latest | models/gemini-4-argon |
| API Protocol | xAI REST API (OpenAI-Compatible) | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2026-07 | 2026-09 |
| Knowledge Cutoff | Real-time (Up to October 2026) | June 2026 |
| Architecture | Colossus-Scale Dense Mixture-of-Experts | Pathways Multimodal Sparse Mixture-of-Experts |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($2.5/1M in) across full 1000K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.25/1M tokens | Implicit + Explicit Context Caching at $0.1/1M with configurable TTL |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| 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 | Real-time Web & X (Twitter) Search Grounding + Code Execution | Built-in Google Search Grounding + Managed Python Code Execution Sandbox |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Vertex AI Supervised Adapter Tuning & Context Distillation |
| Multimodal Token Billing | Text 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 VRAM | Cloud-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 Classification | xAI Production Safety & Alignment Verified | Google DeepMind Frontier Safety Framework Verified |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision | text, vision, audio, video |
| Output Modalities | text | text |
Grok-4 vs Gemini 4 Argon: Quick Answers
Which is more intelligent, Grok-4 or Gemini 4 Argon?
Gemini 4 Argon is more intelligent. It scores 97 compared with 92 on the composite Intelligence Index.
Which model is faster?
Grok-4 is faster, generating 125 tokens per second compared with 115 tokens per second.
Which model is cheaper to run?
Gemini 4 Argon is cheaper at $1.47 per 1M tokens blended, compared with $1.68 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Grok-4 has lower latency, with a time to first token of 0.68s compared with 0.85s.
Verdict
Verdict & Model Selection Recommendation: Choose Grok-4 if your priority is Breaking news analysis, real-time market sentiment, coding, and fast multimodal reasoning. Its performance in demanding tasks justifies its operational token cost. Choose Gemini 4 Argon if your workflow prioritizes Whole-repository code generation, full-book synthesis, video understanding, and multi-hour audio processing. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Frequently asked questions
How does Grok-4 compare to Gemini 4 Argon in API token pricing and cost per token?+
Grok-4 costs $2.50 per 1M input tokens and $10.00 per 1M output tokens, whereas Gemini 4 Argon costs $2.00 input and $10.00 output. Overall, Gemini 4 Argon 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: Grok-4 or Gemini 4 Argon?+
Both Grok-4 and Gemini 4 Argon offer an identical context window of 1,000K tokens (~750k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.
Which AI model is better for software engineering and coding: Grok-4 or Gemini 4 Argon?+
Grok-4 scores 76.5% on SWE-bench Verified while Gemini 4 Argon scores 81.9%. For autonomous software engineering and multi-file debugging, Gemini 4 Argon holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Grok-4 and Gemini 4 Argon?+
Grok-4 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Gemini 4 Argon provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Grok-4 and Gemini 4 Argon?+
Grok-4 generates approximately 125 tokens per second, while Gemini 4 Argon delivers 115 tokens per second. In latency-sensitive production environments, Grok-4 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Grok-4 and Gemini 4 Argon to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Gemini 4 Argon to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Grok-4. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
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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.
Sources: GetInfoUs Independent AI Benchmarks & Official API Specs