Update README.md

README.md

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----
-license: apache-2.0
----
+---
+pipeline_tag: text-generation
+inference: false
+license: apache-2.0
+library_name: transformers
+tags:
+- language
+- aquif
+- text-generation-inference
+- math
+- coding
+- small
+- aquif-3.5
+language:
+- en
+- de
+- it
+- pt
+- fr
+- hi
+- es
+- th
+- zh
+- ja
+---
+
+# aquif-3.5
+
+The aquif-3.5 series is the successor to aquif-3, featuring a simplified naming scheme, expanded Mixture of Experts (MoE) options, and across-the-board performance improvements. This release streamlines model selection while delivering enhanced capabilities across reasoning, multilingual support, and general intelligence tasks.
+
+## Release dates
+- A0.6B, 3B, 7B: August 30th, 2025
+- 8B-Think, A4B-Think: September 1st, 2025
+
+## Model Repository Links
+
+| Model | HuggingFace Repository |
+|-------|----------------------|
+| aquif-3.5-A0.6B-Preview | [aquiffoo/aquif-3.5-A0.6B-Preview](https://huggingface.co/aquiffoo/aquif-3.5-A0.6B-Preview) |
+| aquif-3.5-3B | [aquiffoo/aquif-3.5-3B](https://huggingface.co/aquiffoo/aquif-3.5-3B) |
+| aquif-3.5-7B | [aquiffoo/aquif-3.5-7B](https://huggingface.co/aquiffoo/aquif-3.5-7B) |
+| aquif-3.5-8B-Think | [aquiffoo/aquif-3.5-8B-Think](https://huggingface.co/aquiffoo/aquif-3.5-8B-Think) |
+| aquif-3.5-A4B-Think | [aquiffoo/aquif-3.5-A4B-Think](https://huggingface.co/aquiffoo/aquif-3.5-A4B-Think) |
+
+## Model Overview
+
+| Model | Size (B) | Active Params (B) | Reasoning | MoE | Multilingual | MMLU | Context Window |
+|-------|----------|-------------------|-----------|-----|--------------|------|----------------|
+| aquif-3.5-A0.6B | 2.61 | 0.6 | ❌ | ✅ | ✅ | 60.5% | 4k |
+| aquif-3.5-3B | 2.67 | 2.67 | ❌ | ❌ | ✅ | 70.2% | 32k |
+| aquif-3.5-7B | 7.3 | 7.3 | ❌ | ❌ | ✅ | 78.5% | 16k |
+| aquif-3.5-8B-Think | 8.2 | 8.2 | ✅ | ❌ | ✅ | 81.1% | 40k |
+| aquif-3.5-A4B-Think | 12 | 4 | ✅ | ✅ | ✅ | 86.9% | 128k |
+
+## Model Details
+
+### aquif-3.5-A0.6B (Experimental MoE)
+
+An experimental small-scale Mixture of Experts model designed for multilingual applications with minimal computational overhead. Despite its compact active parameter count, it demonstrates competitive performance against larger dense models.
+
+**Performance Comparison:**
+
+| Metric | aquif-3.5 (2.6B A0.6B) | Qwen3 (0.8B) | LFM2 (0.7B) | aquif-3 (0.4B) |
+|--------|------------------------|--------------|-------------|----------------|
+| MMLU | 60.5 | 44.9 | 49.9 | 55.6 |
+| GPQA | 30.2 | 22.1 | 28.5 | 28.5 |
+| GSM8K | 50.7 | 36.5 | 46.4 | 52.1 |
+| HumanEval | 45.2 | 36.0 | 40.0 | 37.4 |
+| **Average** | **46.7** | **34.9** | **41.2** | **43.4** |
+
+### aquif-3.5-3B (State-of-the-Art Dense)
+
+The new standard for small dense models, offering optimal performance-per-parameter efficiency for general-purpose applications.
+
+**Performance Comparison:**
+
+| Metric | aquif-3.5 (2.7B) | EXAONE 3.5 (2.4B) | Qwen3 (4B) | Gemma 3 (4B) | Phi-4-mini (3.8B) | Apriel-5B-Instruct (4.8B) | aquif-3 (3.2B) |
+|--------|------------------|-------------------|------------|--------------|-------------------|---------------------------|----------------|
+| MMLU (General Knowledge) | 70.2 | 60.4 | 70.4 | 59.6 | 67.3 | 64.6 | 67.5 |
+| GPQA Diamond (Science) | 35.8 | 28.4 | 39.3 | 30.9 | 25.2 | 28.4 | 36.1 |
+| LiveCodeBench (Coding) | 23.1 | 12.5 | 21.3 | 11.2 | 10.4 | 11.6 | 15.4 |
+| IFEval (Instruction Following) | 78.9 | 73.6 | 71.2 | 80.2 | 68.6 | 80.8 | 78.9 |
+| AIME 2025 (Competition Math) | 13.4 | 4.5 | 9.8 | 12.7 | 5.3 | 4.3 | 9.6 |
+| **Average** | **44.3** | **35.9** | **42.4** | **38.9** | **35.4** | **37.9** | **41.5** |
+
+### aquif-3.5-7B (Multilingual Long Context)
+
+A Qwen-based architecture optimized for multilingual applications with extended context capabilities, delivering state-of-the-art performance in its size class.
+
+**Performance Comparison:**
+
+| Metric | aquif-3.5 (7.3B) | EXAONE 3.5 (7.8B) | Qwen3 (8.2B) | Gemma 3 (12B) | Llama 3.1 (8B) | Kanana 1.5 (8B) | aquif-3 (3.2B) |
+|--------|------------------|-------------------|-------------|---------------|----------------|-----------------|----------------|
+| MMLU (General Knowledge) | 78.5 | 72.2 | 82.9 | 74.5 | 69.2 | 68.8 | 67.5 |
+| GPQA Diamond (Science) | 42.3 | 39.4 | 39.3 | 40.9 | 32.8 | 37.5 | 36.1 |
+| LiveCodeBench (Coding) | 21.3 | 18.0 | 23.9 | 13.7 | 10.8 | 16.5 | 15.4 |
+| IFEval (Instruction Following) | 85.6 | 82.6 | 85.4 | 80.2 | 75.0 | 80.1 | 78.9 |
+| AIME 2025 (Competition Math) | 23.4 | 18.3 | 20.9 | 18.8 | 2.7 | 13.4 | 9.6 |
+| **Average** | **50.2** | **46.1** | **50.4** | **45.6** | **38.1** | **43.3** | **41.5** |
+
+### aquif-3.5-8B-Think & aquif-3.5-A4B-Think (Reasoning Models)
+
+Advanced reasoning-capable models designed for complex problem-solving tasks. The A4B variant leverages MoE architecture for enhanced efficiency while maintaining superior reasoning performance.
+
+**Performance Comparison:**
+
+| Metric | aquif-3.5 (12B A4B) | aquif-3.5 (8B) | Qwen3 Thinking 2507 (31B A3B) | gpt-oss-20b (21B A4B) | Nemotron Nano v2 (9B) | Solar Pro 2 |
+|--------|---------------------|-----------------|-------------------------------|----------------------|----------------------|-------------|
+| MMLU-Pro | 78.5 | 78.1 | 80.5 | 73.6 | 74.2 | 80.5 |
+| GPQA Diamond | 70.8 | 66.8 | 70.7 | 61.7 | 64.0 | 68.7 |
+| AIME 2025 | 84.4 | 81.4 | 56.3 | 61.7 | 69.7 | 61.3 |
+| LiveCodeBench | 66.1 | 61.5 | 70.7 | 72.1 | 71.1 | 61.6 |
+| Humanity's Last Exam | 8.9 | 8.2 | 9.8 | 8.5 | 6.5 | 7.0 |
+| TAU-Bench v2 (avg) | 43.7 | 36.8 | 35.7 | 43.2 | 34.9 | 38.7 |
+| **Average** | **58.7** | **55.5** | **54.0** | **53.5** | **53.4** | **53.0** |
+
+## Key Improvements Over aquif-3
+
+- **Simplified Naming**: Clear size-based nomenclature for easier model selection
+- **Enhanced MoE Support**: Multiple MoE configurations across different model sizes
+- **Reasoning Capabilities**: Dedicated thinking models for complex problem-solving
+- **Extended Context**: Up to 128k context window for long-form applications
+- **Multilingual by Default**: Native multilingual support across all variants
+- **Performance Gains**: 5-15% improvement across benchmarks compared to aquif-3
+
+## Usage Recommendations
+
+- **aquif-3.5-A0.6B**: Experimental applications, resource-constrained environments
+- **aquif-3.5-3B**: General-purpose applications, balanced performance/efficiency
+- **aquif-3.5-7B**: Multilingual applications, long-context tasks
+- **aquif-3.5-8B-Think**: Complex reasoning, scientific analysis
+- **aquif-3.5-A4B-Think**: Advanced reasoning with efficiency optimization
+
+## Technical Specifications
+
+All models support:
+- BF16 and FP16 precision
+- Standard transformer architecture optimizations
+- Efficient attention mechanisms
+- Multi-head attention with optimized KV caching
+
+## Acknowledgements
+
+- **Qwen Team**: Base architecture for 7B, 8B, and 12B-A4B models
+- **Meta Llama Team**: Base architecture for 3B and 2.6B-A0.6B models  
+- **Hugging Face**: Model hosting infrastructure and training libraries
+
+## License
+
+This project is released under the Apache 2.0 License. See LICENSE file for details.
+
+---
+
+*Made in 🇧🇷*
+
+© 2025 aquif AI. All rights reserved.