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Atlassian model v0.4 sees major gains in app compilation

By PulseAugur Editorial · [1 sources] ·

The developer released version 0.4 of their Atlassian model, which is based on Qwen3.8-27B. This iteration significantly improved its ability to generate valid Atlassian Forge apps, increasing the success rate from 12 out of 25 apps in version 0.3 to 21 out of 25. The improvements were achieved by focusing training data on previously failing app types and specific module types that were underrepresented in the dataset. The model's artifacts are publicly available on Hugging Face under the Apache-2.0 license. AI

IMPACT Improves developer productivity for Atlassian Forge apps by enhancing AI-assisted code generation.

RANK_REASON This is a release of a fine-tuned model for a specific platform's development tools, not a frontier model release from a major lab.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Atlassian model v0.4 sees major gains in app compilation

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26 / 100
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Tool
This is a release of a fine-tuned model for a specific platform's development tools, not a frontier model release from a major lab.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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model release, product
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Mihai Perdum ·

    v0.4 of our Atlassian model: 21 of 25 apps compile, and the loop that was a diagram

    <h3> Key takeaways </h3> <ul> <li>v0.4 is round T7 of the same Qwen3.8-27B: complete Forge apps that pass Atlassian's validator, our allow-list and tsc went from 12 of 25 (v0.3) to 21 of 25; valid manifests from 14 to 23; the identifier probe with thinking on from 69% to 85%. Sam…

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