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Ember-1 vs Qwen3.8 Omni Flash

Ember-1 and Qwen3.8 Omni Flash are closely matched at 43.1 and 37.8 on the LLM Stats Score.

Fireworks AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Ember-1 and Qwen3.8 Omni Flash are closely matched on the overall LLM Stats Score at 43.1 and 37.8.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Ember-1

  • you want the most recent training data — it shipped Sep 2026

Choose Qwen3.8 Omni Flash

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem

At a glance

The differences that matter most.

Core performance indexes
43.1
#51
37.8
#79
38.6
#71
32.2
#117
29.7
#44
21.0
#73
Cost, coverage & limits
Benchmark wins
—
—
Input price
$3.00 / M
— / M
Output price
$15.00 / M
— / M
Context window
1,040,000
—

Individual benchmarks

4 reported for Ember-1 · 5 for Qwen3.8 Omni Flash

No common benchmarks found

Ember-1 and Qwen3.8 Omni Flashdon'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

Context Window

Maximum input and output token capacity

Only Ember-1 specifies input context (1,040,000 tokens).

Fireworks AI
Ember-1
Input1,040,000 tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3.8 Omni Flash
Input- tokens
Output- tokens
Thu Oct 08 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3.8 Omni Flash supports multimodal inputs, whereas Ember-1 does not.

Qwen3.8 Omni Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

Ember-1

Text
Images
Audio
Video

Qwen3.8 Omni Flash

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

Ember-1

Proprietary

Closed source

Qwen3.8 Omni Flash

Proprietary

Closed source

Release Timeline

When each model was launched

Ember-1 was released on 2026-09-23, while Qwen3.8 Omni Flash was released on 2026-09-18.

Ember-1 is 0 month newer than Qwen3.8 Omni Flash.

Ember-1

Sep 23, 2026

2 weeks ago

5d newer
Qwen3.8 Omni Flash

Sep 18, 2026

2 weeks ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Ember-1 and Qwen3.8 Omni Flash side-by-side, then vote on the output you prefer.

Ember-1
✓ Preferred
Qwen3.8 Omni Flash
Open in Playground

FAQ

Common questions about Ember-1 vs Qwen3.8 Omni Flash.

Which is better, Ember-1 or Qwen3.8 Omni Flash?

Ember-1 and Qwen3.8 Omni Flash are closely matched on the LLM Stats Score at 43.1 and 37.8. Ember-1 is made by Fireworks AI and Qwen3.8 Omni Flash is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Ember-1 compare to Qwen3.8 Omni Flash in benchmarks?

Ember-1 scores SWE-Bench Verified: 92.2%, Terminal-Bench 2.1: 82.0%, DeepSWE 1.1: 75.2%, Tau2 Airline: 66.0%. Qwen3.8 Omni Flash scores VoiceBench Avg: 91.6%, DailyOmni: 85.1%, MMAU: 81.8%, OmniGAIA: 74.0%, WildClawBench: 71.0%.

What are the context window sizes for Ember-1 and Qwen3.8 Omni Flash?

Ember-1 supports 1.0M tokens and Qwen3.8 Omni Flash supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Ember-1 and Qwen3.8 Omni Flash?

Key differences include LLM Stats Score (43.1 vs 37.8), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

Who makes Ember-1 and Qwen3.8 Omni Flash?

Ember-1 is developed by Fireworks AI and Qwen3.8 Omni Flash is developed by Alibaba Cloud / Qwen Team.