Ember-1 vs LongCat-Flash-Thinking-2601
Ember-1 leads the LLM Stats Score 43.1 to 35.4. LongCat-Flash-Thinking-2601 is 11.4x cheaper per token.
Fireworks AI · Meituan · Updated for 2026
Which is better?
Ember-1 leads the overall LLM Stats Score 43.1 to 35.4, ranking #51 overall.
The models split the 2 individual benchmarks reported for both models evenly.
On price, LongCat-Flash-Thinking-2601 is roughly 11.4x 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 43.1 and ranks #51 on LLM Stats
- your work emphasizes coding and agents — 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 LongCat-Flash-Thinking-2601
- cost matters — it's about 11.4x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
4 reported for Ember-1 · 11 for LongCat-Flash-Thinking-2601
Ember-1 outperforms in 1 benchmarks (SWE-Bench Verified), while LongCat-Flash-Thinking-2601 is better at 1 benchmark (Tau2 Airline).
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, Ember-1 ($3.00/1M tokens) is 10.0x more expensive than LongCat-Flash-Thinking-2601 ($0.30/1M tokens).
For output processing, Ember-1 ($15.00/1M tokens) is 12.5x more expensive than LongCat-Flash-Thinking-2601 ($1.20/1M tokens).
In conclusion, Ember-1 is more expensive than LongCat-Flash-Thinking-2601.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Ember-1 has 2220.0B more parameters than LongCat-Flash-Thinking-2601, making it 396.4% larger.
Context Window
Maximum input and output token capacity
Ember-1 accepts 1,040,000 input tokens compared to LongCat-Flash-Thinking-2601's 128,000 tokens. Only LongCat-Flash-Thinking-2601 specifies output context (128,000 tokens).
License
Usage and distribution terms
Ember-1 is licensed under a proprietary license, while LongCat-Flash-Thinking-2601 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
Ember-1 was released on 2026-09-23, while LongCat-Flash-Thinking-2601 was released on 2026-01-14.
Ember-1 is 8 months newer than LongCat-Flash-Thinking-2601.
Sep 23, 2026
2 weeks ago
8mo newerJan 14, 2026
8 months 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. LongCat-Flash-Thinking-2601 is available from Meituan.
Ember-1
LongCat-Flash-Thinking-2601
Outputs Comparison
Judge for yourself.
Run your own prompts against Ember-1 and LongCat-Flash-Thinking-2601 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ember-1 vs LongCat-Flash-Thinking-2601.