DeepScaleR Description
DeepScaleR is a sophisticated language model comprising 1.5 billion parameters, refined from DeepSeek-R1-Distilled-Qwen-1.5B through the use of distributed reinforcement learning combined with an innovative strategy that incrementally expands its context window from 8,000 to 24,000 tokens during the training process. This model was developed using approximately 40,000 meticulously selected mathematical problems sourced from high-level competition datasets, including AIME (1984–2023), AMC (pre-2023), Omni-MATH, and STILL. Achieving an impressive 43.1% accuracy on the AIME 2024 exam, DeepScaleR demonstrates a significant enhancement of around 14.3 percentage points compared to its base model, and it even outperforms the proprietary O1-Preview model, which is considerably larger. Additionally, it excels on a variety of mathematical benchmarks such as MATH-500, AMC 2023, Minerva Math, and OlympiadBench, indicating that smaller, optimized models fine-tuned with reinforcement learning can rival or surpass the capabilities of larger models in complex reasoning tasks. This advancement underscores the potential of efficient modeling approaches in the realm of mathematical problem-solving.
DeepScaleR Alternatives
BYDFi, previously known as BitYard, stands out as the premier cryptocurrency contracts exchange based in Singapore. We offer secure, user-friendly, and rapid trading services for crypto assets across more than 150 nations. Committed to the principle of “Complex Contracts Simple Trade,” BYDFi strives to deliver the most streamlined trading experience possible for its clients. Our platform features a diverse selection of trading pairs encompassing Crypto, Forex, and Commodities. Users can effortlessly create an account using either their email or mobile number, accessible through both desktop and mobile platforms. Currently, we have over 500,000 users engaging in trading activities from various countries. The platform supports multiple languages, including English, Traditional Chinese, Russian, Japanese, Vietnamese, Korean, Indonesian, and Portuguese. With just 30 seconds needed to initiate trading, you have the flexibility to trade anytime and anywhere. BYDFi is not just a trading platform; it is a comprehensive solution for all your digital asset needs. Join us today and experience the future of trading.
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LeaseAccounting.app is a self-serve IFRS 16 and FRS 102 lease accounting platform built for finance teams who want audit-ready compliance without spreadsheets, implementation consultants, or six-figure setup costs. Made by ZenTreasury Oy in Helsinki, Finland with EU-only data hosting. Designed for SMEs reporting under IFRS 16 or FRS 102 (UK GAAP), typically managing 5 to 50 leases. The platform generates complete lease schedules, journal entries, modifications, remeasurements, terminations, and one-click audit evidence packs from any lease contract. AI-assisted contract extraction reads your PDFs and proposes lease terms with confidence scoring; you approve, and the deterministic calculation engine produces the numbers. Same inputs, same outputs, every time. Zen AI is advisory only and never touches a calculation. Other features: Discount Rate Advisor pulls reference rates from central bank sources and drafts a rate memo for review; continuous compliance monitoring flags indexations due, expiring leases, and overdue reassessments; multi-entity bookkeeping from day one; auditor portal access with activity logging (coming soon); journal export to SAP, Oracle, Dynamics, and NetSuite formats; Azure AD / Entra ID SSO with JIT provisioning. Pricing: free tier covers 2 leases with no credit card required. Paid plans start at €149 per month with no per-seat pricing and generous team access included on every tier. Differentiation: built IFRS-first (not ASC 842-first), EU-hosted, fully implemented FRS 102, and self-serve onboarding. The trusted alternative to spreadsheet-based compliance and consultant-heavy enterprise lease tools.
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DeepCoder
DeepCoder, an entirely open-source model for code reasoning and generation, has been developed through a partnership between Agentica Project and Together AI. Leveraging the foundation of DeepSeek-R1-Distilled-Qwen-14B, it has undergone fine-tuning via distributed reinforcement learning, achieving a notable accuracy of 60.6% on LiveCodeBench, which marks an 8% enhancement over its predecessor. This level of performance rivals that of proprietary models like o3-mini (2025-01-031 Low) and o1, all while operating with only 14 billion parameters. The training process spanned 2.5 weeks on 32 H100 GPUs, utilizing a carefully curated dataset of approximately 24,000 coding challenges sourced from validated platforms, including TACO-Verified, PrimeIntellect SYNTHETIC-1, and submissions to LiveCodeBench. Each problem mandated a legitimate solution along with a minimum of five unit tests to guarantee reliability during reinforcement learning training. Furthermore, to effectively manage long-range context, DeepCoder incorporates strategies such as iterative context lengthening and overlong filtering, ensuring it remains adept at handling complex coding tasks. This innovative approach allows DeepCoder to maintain high standards of accuracy and reliability in its code generation capabilities.
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Phi-4-mini-reasoning
Phi-4-mini-reasoning is a transformer-based language model with 3.8 billion parameters, specifically designed to excel in mathematical reasoning and methodical problem-solving within environments that have limited computational capacity or latency constraints. Its optimization stems from fine-tuning with synthetic data produced by the DeepSeek-R1 model, striking a balance between efficiency and sophisticated reasoning capabilities. With training that encompasses over one million varied math problems, ranging in complexity from middle school to Ph.D. level, Phi-4-mini-reasoning demonstrates superior performance to its base model in generating lengthy sentences across multiple assessments and outshines larger counterparts such as OpenThinker-7B, Llama-3.2-3B-instruct, and DeepSeek-R1. Equipped with a 128K-token context window, it also facilitates function calling, which allows for seamless integration with various external tools and APIs. Moreover, Phi-4-mini-reasoning can be quantized through the Microsoft Olive or Apple MLX Framework, enabling its deployment on a variety of edge devices, including IoT gadgets, laptops, and smartphones. Its design not only enhances user accessibility but also expands the potential for innovative applications in mathematical fields.
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Pricing
Pricing Starts At:
Free
Free Version:
Yes
Integrations
No Integrations at this time
Company Details
Company:
Agentica Project
Year Founded:
2025
Headquarters:
United States
Website:
agentica-project.com
Media
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Product Details
Platforms
Windows
Mac
Linux
On-Premises
Types of Training
Training Docs
Customer Support
Online Support
DeepScaleR Features and Options
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