DeepSeek-V4.1-Flash vs Ember-1
DeepSeek-V4.1-Flash and Ember-1 are closely matched at 50.0 and 42.3 on the LLM Stats Score. DeepSeek-V4.1-Flash is 18.2x cheaper per token.
DeepSeek · Fireworks AI · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash and Ember-1 are closely matched on the overall LLM Stats Score at 50.0 and 42.3.
The models split the 2 individual benchmarks reported for both models evenly.
On price, DeepSeek-V4.1-Flash is roughly 18.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4.1-Flash
- cost matters — it's about 18.2x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Ember-1
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for DeepSeek-V4.1-Flash · 4 for Ember-1
DeepSeek-V4.1-Flash outperforms in 1 benchmarks (Terminal-Bench 2.1), while Ember-1 is better at 1 benchmark (DeepSWE 1.1).
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, DeepSeek-V4.1-Flash ($0.22/1M tokens) is 13.6x cheaper than Ember-1 ($3.00/1M tokens).
For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 22.7x cheaper than Ember-1 ($15.00/1M tokens).
In conclusion, Ember-1 is more expensive than DeepSeek-V4.1-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Ember-1 has 2016.8B more parameters than DeepSeek-V4.1-Flash, making it 264.3% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,040,000 tokens. Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).
Input capabilities
Documented input modalities across available providers
DeepSeek-V4.1-Flash supports multimodal inputs, whereas Ember-1 does not.
DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4.1-Flash
Ember-1
License
Usage and distribution terms
DeepSeek-V4.1-Flash 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-V4.1-Flash was released on 2026-09-10, while Ember-1 was released on 2026-09-23.
Ember-1 is 0 month newer than DeepSeek-V4.1-Flash.
Sep 10, 2026
1 months ago
Sep 23, 2026
3 weeks ago
1w 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-V4.1-Flash is available from Fireworks, DeepInfra, Novita. Ember-1 is available from Fireworks.
DeepSeek-V4.1-Flash
Ember-1
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash and Ember-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash vs Ember-1.