Ember-1 vs Qwen3.8 Max
Ember-1 and Qwen3.8 Max are closely matched at 43.1 and 51.1 on the LLM Stats Score. Qwen3.8 Max is 2.4x cheaper per token.
Fireworks AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Ember-1 and Qwen3.8 Max are closely matched on the overall LLM Stats Score at 43.1 and 51.1.
The models split the 2 individual benchmarks reported for both models evenly.
On price, Qwen3.8 Max is roughly 2.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Ember-1 also accepts a larger context window (1,040,000 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 Ember-1
- you process long inputs — it offers a 1,040,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Qwen3.8 Max
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 2.4x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
4 reported for Ember-1 · 42 for Qwen3.8 Max
Ember-1 outperforms in 1 benchmarks (DeepSWE 1.1), while Qwen3.8 Max is better at 1 benchmark (Terminal-Bench 2.1).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Ember-1 ($3.00/1M tokens) is 1.8x more expensive than Qwen3.8 Max ($1.65/1M tokens).
For output processing, Ember-1 ($15.00/1M tokens) is 3.0x more expensive than Qwen3.8 Max ($4.95/1M tokens).
In conclusion, Ember-1 is more expensive than Qwen3.8 Max.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Ember-1 has 380.0B more parameters than Qwen3.8 Max, making it 15.8% larger.
Context Window
Maximum input and output token capacity
Ember-1 accepts 1,040,000 input tokens compared to Qwen3.8 Max's 256,000 tokens. Only Qwen3.8 Max specifies output context (256,000 tokens).
Input capabilities
Documented input modalities across available providers
Qwen3.8 Max supports multimodal inputs, whereas Ember-1 does not.
Qwen3.8 Max can handle both text and other forms of data like images, making it suitable for multimodal applications.
Ember-1
Qwen3.8 Max
License
Usage and distribution terms
Ember-1 is licensed under a proprietary license, while Qwen3.8 Max uses Qwen3.8-Max License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Qwen3.8-Max License
Open weights
Release Timeline
When each model was launched
Ember-1 was released on 2026-09-23, while Qwen3.8 Max was released on 2026-08-02.
Ember-1 is 2 months newer than Qwen3.8 Max.
Sep 23, 2026
2 weeks ago
1mo newerAug 2, 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
Ember-1 is available from Fireworks. Qwen3.8 Max is available from DeepInfra, Fireworks, Novita, Together.
Ember-1
Qwen3.8 Max
Outputs Comparison
Judge for yourself.
Run your own prompts against Ember-1 and Qwen3.8 Max side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ember-1 vs Qwen3.8 Max.