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About

DeepSeek-V4-Flash is a high-efficiency Mixture-of-Experts (MoE) language model designed for fast, scalable reasoning and text generation. It features 284 billion total parameters with 13 billion activated parameters, delivering strong performance while optimizing computational cost. The model supports an extensive context window of up to one million tokens, enabling it to process large documents and complex workflows with ease. Its hybrid attention architecture enhances long-context efficiency by reducing memory and compute requirements. Trained on over 32 trillion tokens, DeepSeek-V4-Flash demonstrates solid capabilities across knowledge, reasoning, and coding tasks. It is designed for scenarios where speed and efficiency are critical, offering a balance between performance and resource usage. The model also supports multiple reasoning modes, allowing users to adjust between faster outputs and deeper analysis.

About

Muse Wonder is a frontier artificial intelligence model developed by Meta for personal assistance, professional workflows, software development, and autonomous agent tasks. The model combines Active Memory, which retrieves relevant information from previous conversations, with Active Focus, which supports sustained execution of complex, multistep assignments. Muse Wonder can assist with research, document analysis, financial and legal information, software engineering, and business process automation. Its agentic capabilities enable it to work across applications, use contextual information, adapt to obstacles, and request clarification or approval when necessary. The model supports coding activities ranging from small application development to complex software projects involving repeated testing and revision. Muse Wonder is available through the Meta Model API and Muse Code, with additional integration into Meta's Muse assistant planned for future releases.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Developers, startups, and enterprises looking for a cost-efficient, scalable language model for fast inference, long-context processing, and real-world AI applications

Audience

Software developers, AI engineers, researchers, business professionals, knowledge workers, enterprise teams, and individuals seeking advanced AI assistance for complex reasoning, software development, personalized workflows, and autonomous task execution

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$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 Version Supported
Free Trial Not Supported

Pricing

$4 per 1M tokens (input)
Input: $4 per 1M tokens
Output: $20 per 1M tokens
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 5.0 / 5
features 4.0 / 5

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5

Pros & Cons from Real Users

Pros

  • DeepSeek-V4-Flash is really compelling because it feels built for developers who care about performance and cost at the same time. A 1M-token context window, open weights, and a low active-parameter MoE setup make it interesting for repo analysis, long-context coding, document-heavy agents, and high-volume automation.

Cons

  • I would still test it carefully before trusting it in production. Cheap inference is great, but coding agents need reliability, strong tool use, clean multi-file edits, good recovery from mistakes, and consistent behavior over long tasks.

Pros & Cons from Real Users

Pros

  • It feels much better at keeping track of what I am trying to accomplish across longer coding, research, and agent workflows instead of slowly losing the thread. Active Memory is especially useful. The model does a better job carrying important context forward, which makes extended projects feel less like repeatedly briefing a new assistant. I also like the new Active Focus approach. Wonder feels more deliberate about working toward the actual goal instead of getting distracted by side issues, which matters a lot when I give an agent something that takes many steps to finish. The coding ability is strong too. Meta is positioning Wonder against models like GPT-6 Astra and Claude Opus 5.5, and early reporting says it is especially competitive in software development and professional agentic work.

Cons

  • No real cons so far. I am still not sure how efficient pricing is.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

DeepSeek
Founded: 2023
China
deepseek.com

Company Information

Meta
Founded: 2004
United States
meta.ai/

Alternatives

Alternatives

GPT-6 Astra

GPT-6 Astra

OpenAI
DeepSeek-V4

DeepSeek-V4

DeepSeek

Categories

AI Coding Models Supported
AI Models Supported

Categories

AI Coding Models Supported
AI Models Supported
Foundation Models Supported
Multimodal Models Supported

Integrations

Cheaper Inference Supported
OpenClaw Supported
.NET Not Supported
C Not Supported
Claude Agent SDK Not Supported
ClinePass Supported
Codex CLI Not Supported
DeepSeek Harness Supported
Go Not Supported
LangChain Not Supported
LlamaIndex Not Supported
Lua Not Supported
Model Context Protocol (MCP) Not Supported
Muse Code Not Supported
Muse Spark Not Supported
Python Not Supported
Rust Not Supported
Swift Not Supported
Together AI Supported
ZooClaw Supported

Integrations

Cheaper Inference Supported
OpenClaw Supported
.NET Supported
C Supported
Claude Agent SDK Supported
ClinePass Not Supported
Codex CLI Supported
DeepSeek Harness Not Supported
Go Supported
LangChain Supported
LlamaIndex Supported
Lua Supported
Model Context Protocol (MCP) Supported
Muse Code Supported
Muse Spark Supported
Python Supported
Rust Supported
Swift Supported
Together AI Not Supported
ZooClaw Not Supported
Claim DeepSeek-V4-Flash and update features and information
Claim DeepSeek-V4-Flash and update features and information
Claim Muse Wonder and update features and information
Claim Muse Wonder and update features and information