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Atria Dawn Preview vs Command A+

Atria Dawn Preview leads the LLM Stats Score 52.3 to 24.0.

Shanghai AI Laboratory · Cohere · Updated for 2026

Which is better?

Atria Dawn Preview leads the overall LLM Stats Score 52.3 to 24.0, ranking #10 overall.

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

Choose Atria Dawn Preview

  • overall performance matters — it scores 52.3 and ranks #10 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

Choose Command A+

  • you are already invested in the Cohere ecosystem

At a glance

The differences that matter most.

Atria Dawn Preview
Shanghai AI Laboratory
Command A+
Cohere
Core performance indexes
LLM Stats Score
52.3
#10
24.0
#168
Reasoning
50.5
#12
21.5
#179
Coding
36.2
#22
7.3
#185
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
— / M
Output price
— / M
— / M
Context window
—
—

Individual benchmarks

12 reported for Atria Dawn Preview · 15 for Command A+

No common benchmarks found

Atria Dawn Preview and Command A+don'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

Model Size

Parameter count comparison

526.0B diff

Atria Dawn Preview has 526.0B more parameters than Command A+, making it 241.3% larger.

Shanghai AI Laboratory
Atria Dawn Preview
744.0Bparameters
Cohere
Command A+
218.0Bparameters
744.0B
Atria Dawn Preview
218.0B
Command A+

Input capabilities

Documented input modalities across available providers

Command A+ supports multimodal inputs, whereas Atria Dawn Preview does not.

Command A+ can handle both text and other forms of data like images, making it suitable for multimodal applications.

Atria Dawn Preview

Text
Images
Audio
Video

Command A+

Text
Images
Audio
Video

License

Usage and distribution terms

Atria Dawn Preview is licensed under MIT, while Command A+ uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Atria Dawn Preview

MIT

Open weights

Command A+

Apache 2.0

Open weights

Release Timeline

When each model was launched

Atria Dawn Preview was released on 2026-09-11, while Command A+ was released on 2026-05-20.

Atria Dawn Preview is 4 months newer than Command A+.

Atria Dawn Preview

Sep 11, 2026

1 weeks ago

3mo newer
Command A+

May 20, 2026

4 months 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?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Atria Dawn Preview and Command A+ side-by-side, then vote on the output you prefer.

Atria Dawn Preview
✓ Preferred
Command A+
Open in Playground

FAQ

Common questions about Atria Dawn Preview vs Command A+.

Which is better, Atria Dawn Preview or Command A+?

Atria Dawn Preview leads the LLM Stats Score 52.3 to 24.0. Atria Dawn Preview is made by Shanghai AI Laboratory and Command A+ is made by Cohere. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Atria Dawn Preview compare to Command A+ in benchmarks?

Atria Dawn Preview scores DeepSearchQA: 96.0%, BrowseComp: 92.5%, CyberGym: 86.5%, MLE-Bench Lite: 86.2%, WideSearch: 81.9%. Command A+ scores AIME 2025: 90.0%, CharXiv-D: 88.0%, MT-AIME 2025: 86.0%, Tau2 Telecom: 85.0%, WMT24++: 81.0%.

What are the main differences between Atria Dawn Preview and Command A+?

Key differences include LLM Stats Score (52.3 vs 24.0), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Atria Dawn Preview and Command A+?

Atria Dawn Preview is developed by Shanghai AI Laboratory and Command A+ is developed by Cohere.

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