Which model is better: Gemini 2.5 Pro or Llama 4 Maverick?
Llama 4 Maverick is 84.0% cheaper for input tokens ($0.20 vs. $1.25 per 1M tokens) and $0.60 vs. $10.00 for output tokens (6.2x cost advantage). In terms of operational performance, Llama 4 Maverick delivers lower response latency at 135ms TTFT (565ms faster than Gemini 2.5 Pro) with 175 vs. 80 tok/s throughput. Gemini 2.5 Pro leads coding evaluations at 63.8% SWE-bench Verified vs. 62.4% for Llama 4 Maverick and 74.0% 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 2.5 Pro
Llama 4 Maverick
Net Delta / Advantage
Input Cost / 1M Tokens
$1.25
$0.20
Llama 4 Maverick is 6.3x cheaper
Output Cost / 1M Tokens
$10.00
$0.60
Llama 4 Maverick (94.0% lower)
Prompt Cache Read / 1M
$0.313
$0.050
Llama 4 Maverick is 6.3x cheaper
Prompt Cache Write / 1M
$1.25
$0.20
Llama 4 Maverick is 6.3x cheaper
Context Window (Max Output)
1,024k (66k out)
1,049k (33k out)
Llama 4 Maverick (1.0x larger context)
Avg TTFT Response Latency
700ms
135ms
Llama 4 Maverick (565ms faster)
Generation Speed (Throughput)
80 tok/s
175 tok/s
Llama 4 Maverick (+95 tok/s faster)
SWE-bench Verified (Coding)
63.8%
62.4%
Gemini 2.5 Pro (+1.4% lead)
GPQA Diamond (PhD STEM)
74%
73.8%
Gemini 2.5 Pro (+0.2% lead)
MMLU-Pro (Multi-Discipline)
85.2%
84.5%
Gemini 2.5 Pro (+0.7% lead)
MATH-500 (Quantitative Logic)
95%
91%
Gemini 2.5 Pro (+4.0% lead)
Inference Value Score (IVR)
56.8 / 100
77 / 100
Llama 4 Maverick (+20.2 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 2.5 Pro (Google) for long-context document and video analysis, large codebase ingestion, and multimodal reasoning — offering a 1,024k context window, 700ms TTFT, and $1.25/1M input pricing ($0.312/1M cached reads).
Which is cheaper: Gemini 2.5 Pro or Llama 4 Maverick?
Llama 4 Maverick is cheaper at $0.20/1M input tokens ($0.60/1M output) compared to $1.25/1M input ($10.00/1M output) for Gemini 2.5 Pro.
Which model has lower TTFT latency and higher tok/s throughput: Gemini 2.5 Pro or Llama 4 Maverick?
Llama 4 Maverick delivers faster first-token latency at 135ms TTFT (175 tok/s throughput) compared to 700ms TTFT (80 tok/s) for Gemini 2.5 Pro.
How do Gemini 2.5 Pro and Llama 4 Maverick compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Gemini 2.5 Pro scores 63.8% versus 62.4% for Llama 4 Maverick. On GPQA Diamond graduate-level STEM reasoning, Gemini 2.5 Pro scores 74% versus 73.8% for Llama 4 Maverick (and 95% vs 91% on MATH-500).
When should you choose Gemini 2.5 Pro?
Choose Gemini 2.5 Pro (Google) for long-context document and video analysis, large codebase ingestion, and multimodal reasoning — offering a 1,024k context window, 700ms TTFT, and $1.25/1M input pricing ($0.312/1M 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).
