Ember-1 vs Qwen3 Max Thinking
Ember-1 leads the LLM Stats Score 43.1 to 32.8. Qwen3 Max Thinking is 2.5x cheaper per token.
Fireworks AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Ember-1 leads the overall LLM Stats Score 43.1 to 32.8, ranking #51 overall.
In the 1 individual benchmarks reported for both models, Ember-1 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3 Max Thinking is roughly 2.5x 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 reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- 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 Qwen3 Max Thinking
- cost matters — it's about 2.5x cheaper per token
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 · 34 for Qwen3 Max Thinking
Ember-1 outperforms in 1 benchmarks (SWE-Bench Verified), while Qwen3 Max Thinking is better at 0 benchmarks.
Ember-1 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, Ember-1 ($3.00/1M tokens) is 2.5x more expensive than Qwen3 Max Thinking ($1.20/1M tokens).
For output processing, Ember-1 ($15.00/1M tokens) is 2.5x more expensive than Qwen3 Max Thinking ($6.00/1M tokens).
In conclusion, Ember-1 is more expensive than Qwen3 Max Thinking.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Ember-1 has 1780.0B more parameters than Qwen3 Max Thinking, making it 178.0% larger.
Context Window
Maximum input and output token capacity
Ember-1 accepts 1,040,000 input tokens compared to Qwen3 Max Thinking's 256,000 tokens. Only Qwen3 Max Thinking specifies output context (256,000 tokens).
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
Ember-1 was released on 2026-09-23, while Qwen3 Max Thinking was released on 2026-02-13.
Ember-1 is 7 months newer than Qwen3 Max Thinking.
Sep 23, 2026
2 weeks ago
7mo newerFeb 13, 2026
7 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. Qwen3 Max Thinking is available from DeepInfra.
Ember-1
Qwen3 Max Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Ember-1 and Qwen3 Max Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ember-1 vs Qwen3 Max Thinking.