Which model is better: DeepSeek R1 or Llama 4 Maverick?
Llama 4 Maverick is 63.6% cheaper for input tokens ($0.20 vs. $0.55 per 1M tokens) and $0.60 vs. $2.19 for output tokens (2.8x cost advantage). In terms of operational performance, Llama 4 Maverick delivers lower response latency at 135ms TTFT (1315ms faster than DeepSeek R1) with 175 vs. 58 tok/s throughput. Llama 4 Maverick leads coding evaluations at 62.4% SWE-bench Verified vs. 49.2% for DeepSeek R1 and 73.8% vs. 71.5% 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
DeepSeek R1
Llama 4 Maverick
Net Delta / Advantage
Input Cost / 1M Tokens
$0.55
$0.20
Llama 4 Maverick is 2.8x cheaper
Output Cost / 1M Tokens
$2.19
$0.60
Llama 4 Maverick (72.6% lower)
Prompt Cache Read / 1M
$0.140
$0.050
Llama 4 Maverick is 2.8x cheaper
Prompt Cache Write / 1M
$0.55
$0.20
Llama 4 Maverick is 2.8x cheaper
Context Window (Max Output)
131k (33k out)
1,049k (33k out)
Llama 4 Maverick (8.0x larger context)
Avg TTFT Response Latency
1450ms
135ms
Llama 4 Maverick (1315ms faster)
Generation Speed (Throughput)
58 tok/s
175 tok/s
Llama 4 Maverick (+117 tok/s faster)
SWE-bench Verified (Coding)
49.2%
62.4%
Llama 4 Maverick (+13.2% lead)
GPQA Diamond (PhD STEM)
71.5%
73.8%
Llama 4 Maverick (+2.3% lead)
MMLU-Pro (Multi-Discipline)
84%
84.5%
Llama 4 Maverick (+0.5% lead)
MATH-500 (Quantitative Logic)
97.3%
91%
DeepSeek R1 (+6.3% lead)
Inference Value Score (IVR)
64.8 / 100
77 / 100
Llama 4 Maverick (+12.2 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Which is cheaper: DeepSeek R1 or Llama 4 Maverick?
Llama 4 Maverick is cheaper at $0.20/1M input tokens ($0.60/1M output) compared to $0.55/1M input ($2.19/1M output) for DeepSeek R1.
Which model has lower TTFT latency and higher tok/s throughput: DeepSeek R1 or Llama 4 Maverick?
Llama 4 Maverick delivers faster first-token latency at 135ms TTFT (175 tok/s throughput) compared to 1450ms TTFT (58 tok/s) for DeepSeek R1.
How do DeepSeek R1 and Llama 4 Maverick compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek R1 scores 49.2% versus 62.4% for Llama 4 Maverick. On GPQA Diamond graduate-level STEM reasoning, DeepSeek R1 scores 71.5% versus 73.8% for Llama 4 Maverick (and 97.3% vs 91% on MATH-500).
When should you choose DeepSeek R1?
Choose DeepSeek R1 (DeepSeek) for open-weight chain-of-thought reasoning, synthetic data distillation, and complex mathematical verification — offering a 131k context window, 1450ms TTFT, and $0.55/1M input pricing ($0.140/1M 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).
