# Ember-1: Fireworks AI Model Hits Hacker News

> Published 2026-09-27 · https://www.promptzone.com/ingrid_kavanagh/ember-1-fireworks-ai-model-hits-hacker-news-2m04

Fireworks AI released **Ember-1**, a new model announced on the company blog and flagged on [Hacker News](https://fireworks.ai/blog/ember-1) where the thread reached 47 points and 9 comments.

> **Model:** Ember-1 | **Parameters:** not disclosed | **Speed:** not disclosed
> **License:** not disclosed | **Available:** Fireworks platform

## What Ember-1 Is

Ember-1 is positioned as an efficient inference model from Fireworks AI. The announcement focuses on performance for production workloads rather than raw parameter count.

The model integrates into the existing Fireworks serving stack, allowing users to route requests through their managed endpoints.

## Benchmarks and Specs Shared

The source post contains no public numbers for tokens per second, context length, or VRAM usage. Early HN comments note the absence of concrete benchmarks and ask for side-by-side data against open models.

No comparison table is possible yet because the announcement supplies no measurable figures.

## How to Try Ember-1

Developers can access Ember-1 through the Fireworks API playground or by creating an account on the platform. No local download or Hugging Face repo is mentioned in the announcement.

API calls follow the standard OpenAI-compatible format already supported by Fireworks.

## Pros and Cons

- Pros: Managed inference removes hardware setup; integrates with existing Fireworks tooling.
- Cons: No disclosed parameters, speed, or license details; limited community testing data available after the HN post.

## Alternatives and Comparisons

Current options for managed LLM inference include Together AI, Groq, and Fireworks itself. Without published metrics for Ember-1, direct comparison remains impossible.

| Provider | Model Example | Public Benchmarks | Local Option |
|----------|---------------|-------------------|--------------|
| Fireworks | Ember-1 | None listed | No |
| Groq | Llama 3.1 70B | Yes | No |
| Together | Mixtral 8x22B | Yes | No |

## Who Should Use This

Teams already on the Fireworks platform may test Ember-1 for latency-sensitive workloads. Researchers seeking open weights or reproducible local benchmarks should wait for more data.

## Bottom Line

Ember-1 currently offers no public performance numbers, making it difficult to evaluate against existing alternatives until Fireworks releases concrete benchmarks.