DeepSeek-V4.1-Flash vs Muse Ember
DeepSeek-V4.1-Flash and Muse Ember are closely matched at 48.9 and 45.9 on the LLM Stats Score. Muse Ember is 1.6x cheaper per token.
DeepSeek · Meta · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash and Muse Ember are closely matched on the overall LLM Stats Score at 48.9 and 45.9.
In the 2 individual benchmarks reported for both models, Muse Ember wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Muse Ember is roughly 1.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Ember also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4.1-Flash
- you need open weights you can self-host or fine-tune
Choose Muse Ember
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 1.6x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- 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
20 reported for DeepSeek-V4.1-Flash · 6 for Muse Ember
DeepSeek-V4.1-Flash outperforms in 0 benchmarks, while Muse Ember is better at 2 benchmarks (Agents' Last Exam, Terminal-Bench 4.0).
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-V4.1-Flash ($0.22/1M tokens) is 2.2x more expensive than Muse Ember ($0.10/1M tokens).
For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 1.3x more expensive than Muse Ember ($0.50/1M tokens).
In conclusion, DeepSeek-V4.1-Flash is more expensive than Muse Ember.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Ember accepts 1,048,576 input tokens compared to DeepSeek-V4.1-Flash's 1,040,000 tokens. Muse Ember can generate longer responses up to 524,288 tokens, while DeepSeek-V4.1-Flash is limited to 393,216 tokens.
Input capabilities
Documented input modalities across available providers
Both DeepSeek-V4.1-Flash and Muse Ember support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4.1-Flash
Muse Ember
License
Usage and distribution terms
DeepSeek-V4.1-Flash 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-V4.1-Flash was released on 2026-09-10, while Muse Ember was released on 2026-11-09.
Muse Ember is 2 months newer than DeepSeek-V4.1-Flash.
Sep 10, 2026
2 months ago
Nov 9, 2026
3 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-V4.1-Flash is available from Fireworks, DeepInfra, Novita. Muse Ember is available from Meta Model API.
DeepSeek-V4.1-Flash
Muse Ember
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash and Muse Ember side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash vs Muse Ember.