DeepSeek V3.2 vs Llama 4 Maverick
Benchmark, pricing and capability comparison of DeepSeek V3.2 and Llama 4 Maverick.
DeepSeek
- Arena Elo
- 1390
- Context
- 128K
- GPQA
- 79%
- SWE-Bench
- 66%
- Input $/1M
- $0.28
- Output $/1M
- $0.42
Meta
- Arena Elo
- 1340
- Context
- 1,000K
- GPQA
- 70%
- SWE-Bench
- 55%
- Input $/1M
- $0.2
- Output $/1M
- $0.6
Verdict
DeepSeek V3.2 and Llama 4 Maverick differ primarily in three areas: performance, context window, and pricing. DeepSeek V3.2 leads in Arena Elo (1390 vs 1340), indicating stronger overall performance in benchmark evaluations, particularly in reasoning and coding tasks. Llama 4 Maverick compensates with a dramatically larger context window (1,000,000 vs 128,000 tokens), making it better suited for processing extremely long documents or multi-document analysis. In terms of pricing, Llama 4 Maverick offers a lower input cost ($0.20 vs $0.28 per 1M tokens) but a higher output cost ($0.60 vs $0.42 per 1M tokens). Choose DeepSeek V3.2 if you prioritize benchmark performance, stronger reasoning/coding capabilities, and lower output costs, and your use cases involve standard-length contexts. Choose Llama 4 Maverick if you need to process very long documents exceeding 128K tokens, prefer lower input token costs, or require extensive multi-document processing.
DeepSeek V3.2 vs Llama 4 Maverick — FAQ
DeepSeek V3.2 has a higher Arena Elo (1390 vs 1340), suggesting better overall benchmark performance, particularly in reasoning and coding tasks. However, Llama 4 Maverick excels in handling much longer contexts (1M vs 128K tokens), which may be more important for certain use cases like analyzing lengthy documents.