DeepSeek-V4-Pro-0813 vs Muse Ember
DeepSeek-V4-Pro-0813 and Muse Ember are closely matched at 48.9 and 45.9 on the LLM Stats Score. Muse Ember is 8.1x cheaper per token.
DeepSeek · Meta · Updated for 2026
Which is better?
DeepSeek-V4-Pro-0813 and Muse Ember are closely matched on the overall LLM Stats Score at 48.9 and 45.9.
In the 1 individual benchmarks reported for both models, Muse Ember wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Muse Ember is roughly 8.1x 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
- you need open weights you can self-host or fine-tune
Choose Muse Ember
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 8.1x cheaper per token
- you want the most recent training data — it shipped Nov 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
12 reported for DeepSeek-V4-Pro-0813 · 6 for Muse Ember
DeepSeek-V4-Pro-0813 outperforms in 0 benchmarks, while Muse Ember is better at 1 benchmark (Agents' Last Exam).
Muse Ember significantly outperforms across most benchmarks.
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 13.0x more expensive than Muse Ember ($0.10/1M tokens).
For output processing, DeepSeek-V4-Pro-0813 ($2.60/1M tokens) is 5.2x more expensive than Muse Ember ($0.50/1M tokens).
In conclusion, DeepSeek-V4-Pro-0813 is more expensive than Muse Ember.*
* 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. DeepSeek-V4-Pro-0813 can generate longer responses up to 1,048,576 tokens, while Muse Ember is limited to 524,288 tokens.
Input capabilities
Documented input modalities across available providers
Muse Ember supports multimodal inputs, whereas DeepSeek-V4-Pro-0813 does not.
Muse Ember can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-0813
Muse Ember
License
Usage and distribution terms
DeepSeek-V4-Pro-0813 is licensed under MIT, while Muse Ember 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 Ember was released on 2026-11-09.
Muse Ember is 3 months newer than DeepSeek-V4-Pro-0813.
Aug 13, 2026
3 months ago
Nov 9, 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 Ember is available from Meta Model API.
DeepSeek-V4-Pro-0813
Muse Ember
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and Muse Ember side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs Muse Ember.