DeepSeek-R1 is a 671B parameter Mixture-of-Experts (MoE) model with 37B activated parameters per token, trained via large-scale reinforcement learning with a focus on reasoning capabilities. It incorporates two RL stages for discovering improved reasoning patterns and aligning with human preferences, along with two SFT stages for seeding reasoning and non-reasoning capabilities. The model achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks.
Amazon Nova Lite is a versatile multimodal model designed to process text, image, and video inputs, producing text-based outputs. Featuring a 300K-token context window, it is well-suited for real-time interactions, document analysis, and visual question answering. As part of the Amazon Nova foundation models, it supports fine-tuning and distillation, enabling advanced customization.
| DeepSeek-R1 | Nova Lite | |
|---|---|---|
Web Site
| - | |
Provider
| ||
Chat
| ||
Release Date
| ||
Modalities
| text | text images video |
API Providers
| DeepSeek, HuggingFace | Amazon Bedrock |
Knowledge Cut-off Date
| Unknown | Purposefully not disclosed |
Open Source
| Yes | No |
Pricing Input
| $0.55 per million tokens | $0.06 per million tokens |
Pricing Output
| $2.19 per million tokens | $0.24 per million tokens |
MMLU
| 90.8% Pass@1 Source | 80.5% CoT Source |
MMLU-Pro
| 84% EM Source | Not available |
MMMU
| - | Not available |
HellaSwag
| - | Not available |
HumanEval
| - | 85.4% pass@1 Source |
MATH
| - | 73.3% CoT Source |
GPQA
| 71.5% Pass@1 Source | 42% Main Source |
IFEval
| 83.3% Prompt Strict Source | 89.7% Source |
SimpleQA
| - | - |
AIME 2024 | - | - |
AIME 2025 | - | - |
Aider Polyglot
| - | - |
LiveCodeBench v5
| - | - |
Global MMLU (Lite)
| - | - |
MathVista
| - | - |
Mobile Application | - | |
MathArena | ||
| Avg. Score | 82% | - |
AIME 2025 A test based on problems from the American Invitational Mathematics Examination, designed to assess the mathematical skills of models. | 89% | - |
HMMT February 2025 A test based on problems from the Harvard-MIT Mathematics Tournament, February 2025, designed to assess the mathematical skills of models. | 77% | - |
BRUMO 2025 | 92% | - |
SMT 2025 A test based on problems from the Stanford Math Tournament, 2025, designed to assess the mathematical skills of models. | 83% | - |
CMIMC 2025 A test based on problems from the Canadian Mathematical Olympiad, 2025, designed to assess the mathematical skills of models. | 69% | - |
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Comments (1)
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