Ember-1 vs Qwen3 VL 32B Thinking
Ember-1 leads the LLM Stats Score 43.1 to 23.5.
Fireworks AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Ember-1 leads the overall LLM Stats Score 43.1 to 23.5, ranking #51 overall.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Ember-1
- overall performance matters — it scores 43.1 and ranks #51 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you want the most recent training data — it shipped Sep 2026
Choose Qwen3 VL 32B Thinking
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
4 reported for Ember-1 · 47 for Qwen3 VL 32B Thinking
Ember-1 and Qwen3 VL 32B Thinkingdon'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
Model Size
Parameter count comparison
Ember-1 has 2747.0B more parameters than Qwen3 VL 32B Thinking, making it 8324.2% larger.
Context Window
Maximum input and output token capacity
Only Ember-1 specifies input context (1,040,000 tokens).
Input capabilities
Documented input modalities across available providers
Qwen3 VL 32B Thinking supports multimodal inputs, whereas Ember-1 does not.
Qwen3 VL 32B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
Ember-1
Qwen3 VL 32B Thinking
License
Usage and distribution terms
Ember-1 is licensed under a proprietary license, while Qwen3 VL 32B Thinking uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Ember-1 was released on 2026-09-23, while Qwen3 VL 32B Thinking was released on 2025-09-22.
Ember-1 is 12 months newer than Qwen3 VL 32B Thinking.
Sep 23, 2026
2 weeks ago
1.0yr newerSep 22, 2025
1.0 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against Ember-1 and Qwen3 VL 32B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ember-1 vs Qwen3 VL 32B Thinking.