Average Ratings 1 Rating

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features

Average Ratings 1 Rating

Total
ease
features
design

Description

DeepSeek-V4-Flash is an optimized Mixture-of-Experts language model built for efficient large-scale AI workloads and fast inference. With 284 billion total parameters and 13 billion activated parameters, it delivers strong performance while maintaining lower computational demands compared to larger models. The model supports a massive context length of up to one million tokens, making it suitable for handling long-form content and multi-step workflows. Its hybrid attention mechanism improves efficiency by minimizing resource consumption while preserving accuracy. Trained on a dataset exceeding 32 trillion tokens, DeepSeek-V4-Flash performs well across reasoning, coding, and knowledge benchmarks. It offers flexible reasoning modes, enabling users to switch between quick responses and more detailed analytical outputs. The architecture is designed to support agentic workflows and scalable deployment environments. As an open-source model, it provides flexibility for customization and integration. Overall, DeepSeek-V4-Flash is a cost-effective and high-performance solution for modern AI applications.

Description

Muse Spark 1.2 is Meta’s newest coding-focused model, released alongside Muse Code as part of Meta’s AI developer platform. The model improves on Muse Spark 1.1 with stronger code generation, complex debugging, codebase understanding, and full developer workflow performance. Muse Spark 1.2 powers Muse Code, a terminal coding agent that can plan changes, write code, validate results, and coordinate persistent background subagents. The model was co-trained with Muse Code so it performs well inside the agentic coding runtime and tool environment. Its training included scaled coding compute, broader training environment diversity, rejection-sampled harness trajectories, recipe optimizations, and Muse Code toolset integration. Muse Spark 1.2 is designed for long-horizon coding tasks such as whole-repository generation, large end-to-end projects, auto-research, and extended optimization work. It uses planning to sequence work, goal conditioning to stay aligned with the user’s objective, and context compaction to preserve useful knowledge over long sessions. The model also benefits from a self-improvement loop where Muse Spark 1.1 generated challenging coding environments and instruction-following templates for training. By combining coding specialization, agentic workflow support, long-horizon training, subagent compatibility, and Meta Model API availability, Muse Spark 1.2 helps developers build, debug, and optimize software more effectively.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

OpenClaw
C#
C++
Facebook
Go
HTML
JavaScript
Kubernetes
LangChain
Model Context Protocol (MCP)
Muse Code
Muse Spark
Novita AI
Oxlo.ai
PHP
R
Rust
Solidity
Vercel AI Gateway
WhatsApp

Integrations

OpenClaw
C#
C++
Facebook
Go
HTML
JavaScript
Kubernetes
LangChain
Model Context Protocol (MCP)
Muse Code
Muse Spark
Novita AI
Oxlo.ai
PHP
R
Rust
Solidity
Vercel AI Gateway
WhatsApp

Pricing Details

$0.14 per 1M tokens (input)
DeepSeek V4 Flash API pricing per 1 million tokens is $0.14 for regular cache-miss inputs, $0.0028 for cache-hit inputs, and $0.28 for outputs.
Free Trial
Free Version

Pricing Details

$1.25 per 1M tokens (input)
$1.25 per million tokens in input, and $4.25 per million tokens of output
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

DeepSeek

Founded

2023

Country

China

Website

deepseek.com

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

meta.ai

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