DeepSeek-V4-Pro-0813 vs Muse Wonder
DeepSeek-V4-Pro-0813 and Muse Wonder are closely matched at 50.8 and 47.9 on the LLM Stats Score. DeepSeek-V4-Pro-0813 is 4.9x cheaper per token.
DeepSeek · Meta · Updated for 2026
Which is better?
DeepSeek-V4-Pro-0813 and Muse Wonder are closely matched on the overall LLM Stats Score at 50.8 and 47.9.
On price, DeepSeek-V4-Pro-0813 is roughly 4.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Pro-0813
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 4.9x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Muse Wonder
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
12 reported for DeepSeek-V4-Pro-0813 · 16 for Muse Wonder
DeepSeek-V4-Pro-0813 and Muse Wonderdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Pro-0813 ($1.30/1M tokens) is 3.1x cheaper than Muse Wonder ($4.00/1M tokens).
For output processing, DeepSeek-V4-Pro-0813 ($2.60/1M tokens) is 7.7x cheaper than Muse Wonder ($20.00/1M tokens).
In conclusion, Muse Wonder is more expensive than DeepSeek-V4-Pro-0813.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. Only DeepSeek-V4-Pro-0813 specifies output context (1,048,576 tokens).
Input capabilities
Documented input modalities across available providers
Muse Wonder supports multimodal inputs, whereas DeepSeek-V4-Pro-0813 does not.
Muse Wonder can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-0813
Muse Wonder
License
Usage and distribution terms
DeepSeek-V4-Pro-0813 is licensed under MIT, while Muse Wonder uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Muse Wonder was released on 2026-10-12.
Muse Wonder is 2 months newer than DeepSeek-V4-Pro-0813.
Aug 13, 2026
2 months ago
Oct 12, 2026
5 days ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Pro-0813 is available from DeepInfra, DeepSeek, Novita, Together. Muse Wonder is available from Meta Model API.
DeepSeek-V4-Pro-0813
Muse Wonder
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and Muse Wonder side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs Muse Wonder.