DeepSeek-R1 vs Ember-1
Comparing DeepSeek-R1 and Ember-1 across benchmarks, pricing, and capabilities.
DeepSeek · Fireworks AI · Updated for 2026
Which is better?
DeepSeek-R1 and Ember-1 trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek-R1 is roughly 6.3x 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 DeepSeek-R1
- cost matters — it's about 6.3x cheaper per token
- you need open weights you can self-host or fine-tune
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
At a glance
The differences that matter most.
Individual benchmarks
0 reported for DeepSeek-R1 · 4 for Ember-1
DeepSeek-R1 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
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1 ($0.55/1M tokens) is 5.5x cheaper than Ember-1 ($3.00/1M tokens).
For output processing, DeepSeek-R1 ($2.19/1M tokens) is 6.8x cheaper than Ember-1 ($15.00/1M tokens).
In conclusion, Ember-1 is more expensive than DeepSeek-R1.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Ember-1 has 2109.0B more parameters than DeepSeek-R1, making it 314.3% larger.
Context Window
Maximum input and output token capacity
Ember-1 accepts 1,040,000 input tokens compared to DeepSeek-R1's 131,072 tokens. Only DeepSeek-R1 specifies output context (131,072 tokens).
License
Usage and distribution terms
DeepSeek-R1 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 was released on 2025-01-20, while Ember-1 was released on 2026-09-23.
Ember-1 is 20 months newer than DeepSeek-R1.
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.
Provider Availability
DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Ember-1 is available from Fireworks.
DeepSeek-R1
Ember-1
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1 and Ember-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1 vs Ember-1.