Ember-1 vs Llama 3.2 90B Instruct
Ember-1 leads the LLM Stats Score 43.6 to 5.2. Llama 3.2 90B Instruct is 16.6x cheaper per token.
Fireworks AI · Meta · Updated for 2026
Which is better?
Ember-1 leads the overall LLM Stats Score 43.6 to 5.2, ranking #46 overall.
On price, Llama 3.2 90B Instruct is roughly 16.6x 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 Ember-1
- overall performance matters — it scores 43.6 and ranks #46 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you process long inputs — it offers a 1,040,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Llama 3.2 90B Instruct
- cost matters — it's about 16.6x cheaper per token
- 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 · 13 for Llama 3.2 90B Instruct
Ember-1 and Llama 3.2 90B Instructdon'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 8.6x more expensive than Llama 3.2 90B Instruct ($0.35/1M tokens).
For output processing, Ember-1 ($15.00/1M tokens) is 37.5x more expensive than Llama 3.2 90B Instruct ($0.40/1M tokens).
In conclusion, Ember-1 is more expensive than Llama 3.2 90B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Ember-1 has 2690.0B more parameters than Llama 3.2 90B Instruct, making it 2988.9% larger.
Context Window
Maximum input and output token capacity
Ember-1 accepts 1,040,000 input tokens compared to Llama 3.2 90B Instruct's 128,000 tokens. Only Llama 3.2 90B Instruct specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
Llama 3.2 90B Instruct supports multimodal inputs, whereas Ember-1 does not.
Llama 3.2 90B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
Ember-1
Llama 3.2 90B Instruct
License
Usage and distribution terms
Ember-1 is licensed under a proprietary license, while Llama 3.2 90B Instruct uses Llama 3.2.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Llama 3.2
Open weights
Release Timeline
When each model was launched
Ember-1 was released on 2026-09-23, while Llama 3.2 90B Instruct was released on 2024-09-25.
Ember-1 is 24 months newer than Llama 3.2 90B Instruct.
Sep 23, 2026
2 weeks ago
2.0yr newerSep 25, 2024
2.0 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 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic.
Ember-1
Llama 3.2 90B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Ember-1 and Llama 3.2 90B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ember-1 vs Llama 3.2 90B Instruct.