Ember-1 vs Llama 4 Scout
Ember-1 leads the LLM Stats Score 43.1 to 7.8. Llama 4 Scout is 44.4x cheaper per token.
Fireworks AI · Meta · Updated for 2026
Which is better?
Ember-1 leads the overall LLM Stats Score 43.1 to 7.8, ranking #51 overall.
On price, Llama 4 Scout is roughly 44.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 4 Scout also accepts a larger context window (10,000,000 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 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
Choose Llama 4 Scout
- cost matters — it's about 44.4x cheaper per token
- you process long inputs — it offers a 10,000,000 token context window
- 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 · 12 for Llama 4 Scout
Ember-1 and Llama 4 Scoutdon'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, Ember-1 ($3.00/1M tokens) is 37.5x more expensive than Llama 4 Scout ($0.08/1M tokens).
For output processing, Ember-1 ($15.00/1M tokens) is 50.0x more expensive than Llama 4 Scout ($0.30/1M tokens).
In conclusion, Ember-1 is more expensive than Llama 4 Scout.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Ember-1 has 2671.0B more parameters than Llama 4 Scout, making it 2450.5% larger.
Context Window
Maximum input and output token capacity
Llama 4 Scout accepts 10,000,000 input tokens compared to Ember-1's 1,040,000 tokens. Only Llama 4 Scout specifies output context (10,000,000 tokens).
Input capabilities
Documented input modalities across available providers
Llama 4 Scout supports multimodal inputs, whereas Ember-1 does not.
Llama 4 Scout can handle both text and other forms of data like images, making it suitable for multimodal applications.
Ember-1
Llama 4 Scout
License
Usage and distribution terms
Ember-1 is licensed under a proprietary license, while Llama 4 Scout uses Llama 4 Community License Agreement.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Llama 4 Community License Agreement
Open weights
Release Timeline
When each model was launched
Ember-1 was released on 2026-09-23, while Llama 4 Scout was released on 2025-04-05.
Ember-1 is 18 months newer than Llama 4 Scout.
Sep 23, 2026
2 weeks ago
1.5yr newerApr 5, 2025
1.5 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Ember-1 is available from Fireworks. Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together.
Ember-1
Llama 4 Scout
Outputs Comparison
Judge for yourself.
Run your own prompts against Ember-1 and Llama 4 Scout side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ember-1 vs Llama 4 Scout.