DeepSeek R1 Zero vs Ember-1
Ember-1 leads the LLM Stats Score 43.1 to 16.0.
DeepSeek · Fireworks AI · Updated for 2026
Which is better?
Ember-1 leads the overall LLM Stats Score 43.1 to 16.0, ranking #51 overall.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek R1 Zero
- you need open weights you can self-host or fine-tune
Choose Ember-1
- overall performance matters — it scores 43.1 and ranks #51 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Individual benchmarks
4 reported for DeepSeek R1 Zero · 4 for Ember-1
DeepSeek R1 Zero and Ember-1don'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 2109.0B more parameters than DeepSeek R1 Zero, making it 314.3% larger.
Context Window
Maximum input and output token capacity
Only Ember-1 specifies input context (1,040,000 tokens).
License
Usage and distribution terms
DeepSeek R1 Zero is licensed under MIT, while Ember-1 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 R1 Zero was released on 2025-01-20, while Ember-1 was released on 2026-09-23.
Ember-1 is 20 months newer than DeepSeek R1 Zero.
Jan 20, 2025
1.7 years ago
Sep 23, 2026
2 weeks ago
1.7yr newerKnowledge 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 DeepSeek R1 Zero and Ember-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Zero vs Ember-1.