Muse Ember vs Qwen3.8 Flash
Muse Ember and Qwen3.8 Flash are closely matched at 45.9 and 47.4 on the LLM Stats Score. Muse Ember is 1.1x cheaper per token.
Meta · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Muse Ember and Qwen3.8 Flash are closely matched on the overall LLM Stats Score at 45.9 and 47.4.
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 1.1x 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 Muse Ember
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 1.1x 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
Choose Qwen3.8 Flash
- you want predictable pricing at $0.15/M input and $0.47/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
6 reported for Muse Ember · 22 for Qwen3.8 Flash
Muse Ember outperforms in 1 benchmarks (Agents' Last Exam), while Qwen3.8 Flash is better at 0 benchmarks.
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, Muse Ember ($0.10/1M tokens) is 1.5x cheaper than Qwen3.8 Flash ($0.15/1M tokens).
For output processing, Muse Ember ($0.50/1M tokens) is 1.1x more expensive than Qwen3.8 Flash ($0.47/1M tokens).
In conclusion, Qwen3.8 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 Qwen3.8 Flash's 1,000,000 tokens. Muse Ember can generate longer responses up to 524,288 tokens, while Qwen3.8 Flash is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both Muse Ember and Qwen3.8 Flash support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Muse Ember
Qwen3.8 Flash
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
Muse Ember was released on 2026-11-09, while Qwen3.8 Flash was released on 2026-08-26.
Muse Ember is 3 months newer than Qwen3.8 Flash.
Nov 9, 2026
3 days ago
2mo newerAug 26, 2026
2 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Muse Ember is available from Meta Model API. Qwen3.8 Flash is available from Novita.
Muse Ember
Qwen3.8 Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against Muse Ember and Qwen3.8 Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about Muse Ember vs Qwen3.8 Flash.