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DeepSeek-V3.1 vs Llama 3.1 Nemotron Nano 8B
Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V3.1, released by DeepSeek in August 2025, is a hybrid large language model with 671 billion total parameters (37 billion active) that unifies the capabilities of DeepSeek-V3 and DeepSeek-R1 in a single model. It features a 128K token context window and supports both direct generation and extended reasoning modes selectable via the chat template. DeepSeek-V3.1 targets general-purpose tasks, coding, and complex reasoning under an open MIT license.
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NVIDIA
Llama-3.1-Nemotron-Nano-8B-v1 is an 8-billion-parameter model from NVIDIA, developed as a fine-tuned variant of Meta's Llama 3.1 8B using NVIDIA's Nemotron post-training methodology, which applies reinforcement learning and process reward modeling to enhance instruction-following and reasoning capability over the base model. The Nano designation marks it as the entry-level member of the Nemotron family, optimized for efficient inference on a single GPU while delivering meaningfully improved performance on instruction alignment and agentic tasks compared to standard Llama 3.1. Released open-weight on HuggingFace, it is designed for deployment in NVIDIA-accelerated environments and supports NVIDIA NIM for enterprise inference.
7 months newer
Llama 3.1 Nemotron Nano 8B
NVIDIA
2025-01-06
DeepSeek-V3.1
DeepSeek
2025-08-21
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3.1
1 providers
DeepSeek
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Llama 3.1 Nemotron Nano 8B
0 providers
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DeepSeek-V3.1
Avg Score:0.0%
Providers:1
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Llama 3.1 Nemotron Nano 8B
Avg Score:0.0%
Providers:0