DeepSeek-R1-0528 vs Llama 4 Maverick
DeepSeek-R1-0528 leads the LLM Stats Score 24.1 to 14.7. Llama 4 Maverick is 3.3x cheaper per token.
DeepSeek · Meta · Updated for 2026
Which is better?
DeepSeek-R1-0528 leads the overall LLM Stats Score 24.1 to 14.7, ranking #183 overall.
In the 3 individual benchmarks reported for both models, DeepSeek-R1-0528 wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, Llama 4 Maverick is roughly 3.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 4 Maverick also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-R1-0528
- overall performance matters — it scores 24.1 and ranks #183 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- you want the most recent training data — it shipped May 2025
Choose Llama 4 Maverick
- cost matters — it's about 3.3x cheaper per token
- you process long inputs — it offers a 1,000,000 token context window
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
16 reported for DeepSeek-R1-0528 · 13 for Llama 4 Maverick
DeepSeek-R1-0528 outperforms in 3 benchmarks (GPQA, LiveCodeBench, MMLU-Pro), while Llama 4 Maverick is better at 0 benchmarks.
DeepSeek-R1-0528 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) is 2.9x more expensive than Llama 4 Maverick ($0.17/1M tokens).
For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 3.6x more expensive than Llama 4 Maverick ($0.60/1M tokens).
In conclusion, DeepSeek-R1-0528 is more expensive than Llama 4 Maverick.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-R1-0528 has 271.0B more parameters than Llama 4 Maverick, making it 67.8% larger.
Context Window
Maximum input and output token capacity
Llama 4 Maverick accepts 1,000,000 input tokens compared to DeepSeek-R1-0528's 163,840 tokens. Llama 4 Maverick can generate longer responses up to 1,000,000 tokens, while DeepSeek-R1-0528 is limited to 163,840 tokens.
Input capabilities
Documented input modalities across available providers
Llama 4 Maverick supports multimodal inputs, whereas DeepSeek-R1-0528 does not.
Llama 4 Maverick can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1-0528
Llama 4 Maverick
License
Usage and distribution terms
DeepSeek-R1-0528 is licensed under MIT, while Llama 4 Maverick uses Llama 4 Community License Agreement.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Llama 4 Community License Agreement
Open weights
Release Timeline
When each model was launched
DeepSeek-R1-0528 was released on 2025-05-28, while Llama 4 Maverick was released on 2025-04-05.
DeepSeek-R1-0528 is 2 months newer than Llama 4 Maverick.
May 28, 2025
1.4 years ago
1mo newerApr 5, 2025
1.5 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita. Llama 4 Maverick is available from DeepInfra, Novita, Lambda, Groq, Fireworks, Together, Sambanova.
DeepSeek-R1-0528
Llama 4 Maverick
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1-0528 and Llama 4 Maverick side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1-0528 vs Llama 4 Maverick.