DeepSeek-V4-Flash-0731 vs Ember-1
DeepSeek-V4-Flash-0731 and Ember-1 are closely matched at 43.0 and 42.3 on the LLM Stats Score. DeepSeek-V4-Flash-0731 is 66.7x cheaper per token.
DeepSeek · Fireworks AI · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0731 and Ember-1 are closely matched on the overall LLM Stats Score at 43.0 and 42.3.
In the 1 individual benchmarks reported for both models, DeepSeek-V4-Flash-0731 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4-Flash-0731 is roughly 66.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-0731 also accepts a larger context window (1,048,576 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-V4-Flash-0731
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 66.7x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- 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
9 reported for DeepSeek-V4-Flash-0731 · 4 for Ember-1
DeepSeek-V4-Flash-0731 outperforms in 1 benchmarks (Terminal-Bench 2.1), while Ember-1 is better at 0 benchmarks.
DeepSeek-V4-Flash-0731 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.06/1M tokens) is 50.0x cheaper than Ember-1 ($3.00/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 83.3x cheaper than Ember-1 ($15.00/1M tokens).
In conclusion, Ember-1 is more expensive than DeepSeek-V4-Flash-0731.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Ember-1 has 2476.0B more parameters than DeepSeek-V4-Flash-0731, making it 814.5% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0731 accepts 1,048,576 input tokens compared to Ember-1's 1,040,000 tokens. Only DeepSeek-V4-Flash-0731 specifies output context (1,048,576 tokens).
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 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-Flash-0731 was released on 2026-07-31, while Ember-1 was released on 2026-09-23.
Ember-1 is 2 months newer than DeepSeek-V4-Flash-0731.
Jul 31, 2026
2 months ago
Sep 23, 2026
3 weeks ago
1mo 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-Flash-0731 is available from DeepInfra, Novita, Fireworks. Ember-1 is available from Fireworks.
DeepSeek-V4-Flash-0731
Ember-1
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and Ember-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Ember-1.