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.
GPT-4.1 Nano, launched by OpenAI on April 14, 2025, is the company's fastest and most affordable model to date. Designed for low-latency tasks such as classification, autocomplete, and fast inference scenarios, it combines compact architecture with robust capabilities. Despite its size, it supports an impressive 1 million token context window and delivers strong benchmark results, achieving 80.1% on MMLU and 50.3% on GPQA. With a knowledge cutoff of June 2024, GPT-4.1 Nano offers exceptional value at just $0.10 per million input tokens and $0.40 per million output tokens, with a 75% discount applied to cached inputs, making it ideal for high-volume, cost-sensitive deployments.
| DeepSeek-R1 | GPT-4.1 Nano | |
|---|---|---|
Web Site
| ||
Provider
| ||
Chat
| ||
Release Date
| ||
Modalities
| text | text images |
API Providers
| DeepSeek, HuggingFace | OpenAI API |
Knowledge Cut-off Date
| Unknown | - |
Open Source
| Yes | No |
Pricing Input
| $0.55 per million tokens | $0.10 per million tokens |
Pricing Output
| $2.19 per million tokens | $0.40 per million tokens |
MMLU
| 90.8% Pass@1 Source | 80.1% Source |
MMLU-Pro
| 84% EM Source | - |
MMMU
| - | 55.4% Source |
HellaSwag
| - | - |
HumanEval
| - | - |
MATH
| - | - |
GPQA
| 71.5% Pass@1 Source | 50.3% Diamond Source |
IFEval
| 83.3% Prompt Strict Source | 74.5% Source |
SimpleQA
| - | - |
AIME 2024 | - | 29.4% Source |
AIME 2025 | - | - |
Aider Polyglot
| - | - |
LiveCodeBench v5
| - | - |
Global MMLU (Lite)
| - | 66.9% Source |
MathVista
| - | 56.2% Image Reasoning Source |
Mobile Application |
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