Claude Mythos 5.1 vs Gemini 4 Argon
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Claude Mythos 5.1 by Anthropic 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, Gemini 4 Argon is more economical per million generated tokens. 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, Gemini 4 Argon 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.
Switch & Compare Any Models
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Claude Mythos 5.1
Restricted FrontierAnthropic's restricted frontier capability tier (Project Glasswing), shared exclusively with vetted national cybersecurity and life-science research organizations.
$15.00 / 1M
$75.00 / 1M
1M tokens
84.2%
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 7.6x cheaper for API usage (input + output tokens combined).
- Gemini 4 Argon is faster at 115 tok/s vs 60 tok/s.
- Claude Mythos 5.1 leads on SWE-bench coding (84.2% vs 81.9%).
| Feature | Claude Mythos 5.1 | Gemini 4 Argon |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 88 | 97 |
Provider | Anthropic | |
Input Price Cost per million input tokens | $15.00 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $75.00 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $11.55 / 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 | 128K | 1000K |
Throughput Speed Tokens generated per second | 60 tok/s | 115 tok/s |
SWE-bench Verified Real-world software engineering | 84.2% | 81.9% |
GPQA Diamond Graduate-level reasoning | 82% | 81.5% |
Cached Input Price Prompt caching discount per 1M tokens | $1.50 / 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.
Claude Mythos 5.1 · Strengths & Key Advantages
- State-of-the-art capability under Project Glasswing for autonomous biological and cyber defense
- Superhuman code synthesis and multi-repository vulnerability validation
- Extreme rigor in formal logical reasoning
Considerations & Trade-offs
- Gated access: strictly unavailable to the general public or unvetted commercial entities
- Stringent compliance oversight and continuous human-in-the-loop audit logs required
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 | Claude Mythos 5.1 | Gemini 4 Argon |
|---|---|---|
Cost per Task Estimated USD to finish one task | $16.46 | $2.45 |
Output Tokens / Task Tokens generated per task | 72K | 75K |
Reasoning Tokens / Task Thinking tokens burned per task | 37K | 36K |
Technical Specifications
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude Mythos 5.1 | Gemini 4 Argon |
|---|---|---|
| Official API Model ID (SDK) | claude-mythos-5-1-20260901 | models/gemini-4-argon |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2026-09 | 2026-09 |
| Knowledge Cutoff | June 2026 | June 2026 |
| Architecture | Restricted Frontier Autonomous Cognitive System | Pathways Multimodal Sparse Mixture-of-Experts |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 4,000 – 10,000 RPM (Tier 4 + Priority 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) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | $1.5/1M cached read (90% off); 5-min default & 1-hour extended TTL | 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 | Native Web Search Citations + Code Execution Tool + MCP Connectors | Built-in Google Search Grounding + Managed Python Code Execution Sandbox |
| Official Fine-Tuning Support | Custom Model Tuning via Amazon Bedrock & Prompt 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 | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated | 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 |
Claude Mythos 5.1 vs Gemini 4 Argon: Quick Answers
Which is more intelligent, Claude Mythos 5.1 or Gemini 4 Argon?
Gemini 4 Argon is more intelligent. It scores 97 compared with 88 on the composite Intelligence Index.
Which model is faster?
Gemini 4 Argon is faster, generating 115 tokens per second compared with 60 tokens per second.
Which model is cheaper to run?
Gemini 4 Argon is cheaper at $1.47 per 1M tokens blended, compared with $11.55 (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 1.60s.
Verdict
Verdict & Model Selection Recommendation: Choose Claude Mythos 5.1 if your priority is National defense cybersecurity hardening, advanced biological countermeasures, and frontier safety research. 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 Claude Mythos 5.1 compare to Gemini 4 Argon in API token pricing and cost per token?+
Claude Mythos 5.1 costs $15.00 per 1M input tokens and $75.00 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: Claude Mythos 5.1 or Gemini 4 Argon?+
Both Claude Mythos 5.1 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: Claude Mythos 5.1 or Gemini 4 Argon?+
Claude Mythos 5.1 scores 84.2% on SWE-bench Verified while Gemini 4 Argon scores 81.9%. For autonomous software engineering and multi-file debugging, Claude Mythos 5.1 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Claude Mythos 5.1 and Gemini 4 Argon?+
Claude Mythos 5.1 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 Claude Mythos 5.1 and Gemini 4 Argon?+
Claude Mythos 5.1 generates approximately 60 tokens per second, while Gemini 4 Argon delivers 115 tokens per second. In latency-sensitive production environments, Gemini 4 Argon provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Claude Mythos 5.1 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 Claude Mythos 5.1. 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
- Claude Mythos 5.1 vs Claude Opus 5.5: Benchmarks, Pricing & Speed ComparisonCompare
- Claude Mythos 5.1 vs GPT-6 Astra: Benchmarks, Pricing & Speed ComparisonCompare
- Claude Opus 5.5 vs Gemini 4 Argon: Benchmarks, Pricing & Speed ComparisonCompare
- Claude Sonnet 5.5 vs Gemini 4 Argon: Benchmarks, Pricing & Speed ComparisonCompare
- Command A Plus vs Gemini 4 Argon: Benchmarks, Pricing & Speed ComparisonCompare
- DeepSeek V4.1-Flash vs Gemini 4 Argon: Benchmarks, Pricing & Speed ComparisonCompare
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