Past battle · 2026-02-20 UTC
LLM Showdown — February 20, 2026
From the LLM category. 14 marks placed across 3 fighters. DeepSeek R1 took the crown.
Final standings
The line-up
The fighters
Profiles of every tool that competed in this battle, ranked by their final score.
DeepSeek R1
An open-source large language model excelling in reasoning, math, and coding tasks with MIT licensing for free use and modification.
DeepSeek R1 is an open-source large language model that excels in reasoning, math, and coding tasks. It utilizes a Mixture of Experts (MoE) architecture with 37B active parameters and 671B total parameters, supporting 128K context length. The model incorporates advanced reinforcement learning techniques to achieve self-verification, multi-step reflection, and human-aligned reasoning capabilities. DeepSeek R1 has achieved state-of-the-art performance in various benchmarks, including 97.3% accuracy on MATH-500, 79.8% pass rate on AIME 2024, and outperforming 96.3% of Codeforces participants. The model is available in multiple variants, ranging from 1.5B to 70B parameters, and is licensed under MIT for free use and modification. DeepSeek R1 can be used online for free, and a WebGPU-accelerated version can run locally in a browser. The model is designed for complex problem-solving, multilingual understanding, and production-grade code generation. Its strengths include exceptional mathematical reasoning, code generation, and natural language understanding capabilities. However, as an open-source model, it may require technical expertise to deploy and fine-tune for specific use cases. DeepSeek R1 is positioned among the top-performing AI models globally, with capabilities comparable to leading proprietary solutions. Its open-source nature allows for community-driven development and continuous upgrades, including planned multimodal support, conversational enhancement, and distributed inference optimization. The model has a pure reinforcement learning development, which allows it to achieve GPT-4-level math performance at a significantly lower cost. The chain-of-thought visualization capability addresses AI "black box" challenges, providing insights into the model's reasoning process. DeepSeek R1's API offers an OpenAI-compatible endpoint for integration, priced at $0.14 per million tokens. The model's weights are open-source, allowing for commercial use and modification.
Criteria breakdown
- Mixture of Experts (MoE) architecture
- Advanced reinforcement learning techniques
- Self-verification and multi-step reflection capabilities
- Human-aligned reasoning
- Support for 128K context length
- OpenAI-compatible API endpoint
Pixtral 12B 24.09
Open multimodal 12B model handling interleaved images and text with a 128K context window.
Pixtral 12B 24.09 is a multimodal model from Mistral AI that processes both images and text within a single sequence, supporting variable image sizes and aspect ratios. It uses a 12-billion-parameter language decoder paired with a vision encoder, enabling tasks like visual question answering, document understanding, chart interpretation, and image captioning. The model accepts up to a 128K token context, allowing multiple images to be interleaved with long-form text in one prompt. Released under an open license, it can be deployed locally or through inference providers, making it suitable for developers building vision-language applications, research workflows, and multimodal agents.
Criteria breakdown
- 12B parameter vision-language model
- Interleaved image and text inputs
- 128K token context length
- Native variable image size support
- Open-weight release
- Suitable for OCR, VQA, and captioning
DeepSeek V3
Open-source mixture-of-experts model offering GPT-4o-level reasoning at a fraction of the cost.
DeepSeek V3 is a large-scale mixture-of-experts (MoE) language model developed by DeepSeek AI. It activates only a subset of its total parameters per token, allowing it to deliver strong performance in reasoning, mathematics, and coding tasks while keeping inference costs significantly lower than comparable dense models. Released with open weights, DeepSeek V3 has become a popular choice for developers and researchers who need a capable foundation model they can self-host, fine-tune, or integrate via API. Benchmarks place it competitively against leading proprietary models like GPT-4o, particularly on math and logical reasoning evaluations. The model is well suited for technical assistants, code generation pipelines, research workflows, and any application where reasoning quality and budget efficiency both matter.
Criteria breakdown
- Mixture-of-experts architecture
- Competitive reasoning and math benchmarks
- Open-source model weights
- API access via DeepSeek platform
- Long context window support
- Fine-tuning friendly