Which model is better: Gemini 4 Argon or Llama 4 Maverick?
Llama 4 Maverick is 90.0% cheaper for input tokens ($0.20 vs. $2.00 per 1M tokens) and $0.60 vs. $10.00 for output tokens (10.0x cost advantage). In terms of operational performance, Llama 4 Maverick delivers lower response latency at 135ms TTFT (715ms faster than Gemini 4 Argon) with 175 vs. 115 tok/s throughput. Gemini 4 Argon leads coding evaluations at 84.5% SWE-bench Verified vs. 62.4% for Llama 4 Maverick and 93.8% vs. 73.8% on GPQA Diamond.
Verified daily via automated API latency tests and official documentation.
Zero-Shot RAG Verified
Verified Performance & Unit Economics Delta (12 Dimensions)
Daily synchronized metrics across token pricing, prompt cache economics, latency, throughput, and 5 capability benchmarks.
Metric / Dimension
Gemini 4 Argon
Llama 4 Maverick
Net Delta / Advantage
Input Cost / 1M Tokens
$2.00
$0.20
Llama 4 Maverick is 10.0x cheaper
Output Cost / 1M Tokens
$10.00
$0.60
Llama 4 Maverick (94.0% lower)
Prompt Cache Read / 1M
$0.100
$0.050
Llama 4 Maverick is 2.0x cheaper
Prompt Cache Write / 1M
$0.50
$0.20
Llama 4 Maverick is 2.5x cheaper
Context Window (Max Output)
1,024k (1000k out)
1,049k (33k out)
Llama 4 Maverick (1.0x larger context)
Avg TTFT Response Latency
850ms
135ms
Llama 4 Maverick (715ms faster)
Generation Speed (Throughput)
115 tok/s
175 tok/s
Llama 4 Maverick (+60 tok/s faster)
SWE-bench Verified (Coding)
84.5%
62.4%
Gemini 4 Argon (+22.1% lead)
GPQA Diamond (PhD STEM)
93.8%
73.8%
Gemini 4 Argon (+20.0% lead)
MMLU-Pro (Multi-Discipline)
91.4%
84.5%
Gemini 4 Argon (+6.9% lead)
MATH-500 (Quantitative Logic)
98.2%
91%
Gemini 4 Argon (+7.2% lead)
Inference Value Score (IVR)
62.6 / 100
77 / 100
Llama 4 Maverick (+14.4 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose Gemini 4 Argon (Google) for engineered with a 1M output token limit for long-horizon software engineering, cybersecurity vulnerability remediation, and deep multimodal enterprise work across legal and financial domains — offering a 1,024k context window, 850ms TTFT, and $2.00/1M input pricing ($0.100/1M cached reads).
Which is cheaper: Gemini 4 Argon or Llama 4 Maverick?
Llama 4 Maverick is cheaper at $0.20/1M input tokens ($0.60/1M output) compared to $2.00/1M input ($10.00/1M output) for Gemini 4 Argon.
Which model has lower TTFT latency and higher tok/s throughput: Gemini 4 Argon or Llama 4 Maverick?
Llama 4 Maverick delivers faster first-token latency at 135ms TTFT (175 tok/s throughput) compared to 850ms TTFT (115 tok/s) for Gemini 4 Argon.
How do Gemini 4 Argon and Llama 4 Maverick compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Gemini 4 Argon scores 84.5% versus 62.4% for Llama 4 Maverick. On GPQA Diamond graduate-level STEM reasoning, Gemini 4 Argon scores 93.8% versus 73.8% for Llama 4 Maverick (and 98.2% vs 91% on MATH-500).
When should you choose Gemini 4 Argon?
Choose Gemini 4 Argon (Google) for engineered with a 1M output token limit for long-horizon software engineering, cybersecurity vulnerability remediation, and deep multimodal enterprise work across legal and financial domains — offering a 1,024k context window, 850ms TTFT, and $2.00/1M input pricing ($0.100/1M cached reads).
When should you choose Llama 4 Maverick?
Choose Llama 4 Maverick (Meta) for high-throughput open-weight multimodal assistants, enterprise RAG, and low-cost cloud inference on Groq and Cerebras — offering a 1,048k context window, 135ms TTFT, and $0.20/1M input pricing ($0.050/1M cached reads).
