| ## patner resources |
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| ### OpenBMB |
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| The MiniCPM family of models are tiny and highly capable models for a variety of usecases spanning many test, vision, and audio. |
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| Includes MiniCPM 1B (ultra-fast local text), MiniCPM 4.18B (deep reasoning), MiniCPM-V 4.6 (1.3B param vision/document assistant), and MiniCPM-o 4.5 (world's first full-duplex omni-model for natural text/audio/vision). |
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| OpenBMB have provided free API access to use these models. |
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| API endpoints: |
| - **MiniCPM4.1-8B**: http://35.203.155.71:8001 |
| - **MiniCPM-V-4.5**: http://35.203.155.71:8002 |
| - **MiniCPM-V-4.6**: http://35.203.155.71:8003 |
| - **MiniCPM-V-4.6-Thinking**: http://35.203.155.71:8004\ |
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| Authorization: |
| ``` |
| Bearer sk-minicpm-V8bcD-YTAMxECagaKOnbwTCN69|IN2LhSezGOgq2Ues |
| ``` |
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| These models can also be run locally on most hardware via llama.cpp or transformers. |
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| #### Recommended MiniCPM Models |
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| The following models are recommended for participants building with MiniCPM models. Participants may also use other rule-compliant MiniCPM series models as long as they comply with the hackathon’s model-size requirements. |
| Model Best For Link |
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| OpenBMB Model Collections |
| Central entry point for all OpenBMB / MiniCPM |
| models on Hugging Face |
| https://huggingface.co/openbmb/collections |
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| MiniCPM-V 4.6 |
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| Image understanding, video understanding, OCR, document understanding, multimodal apps |
| https://huggingface.co/openbmb/MiniCPM-V-4.6 |
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| MiniCPM-o 4.5 |
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| Omni-modal interaction, voice + vision + |
| language, real-time multimodal experiences |
| https://huggingface.co/openbmb/MiniCPM-o-4_5 |
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| MiniCPM-V 4.5 |
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| Strong multimodal understanding, |
| image/video use cases, visual reasoning |
| https://huggingface.co/openbmb/MiniCPM-V-4_5 |
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| MiniCPM5-1B |
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| Lightweight text generation, local-first apps, |
| on-device assistants, small LLM use cases |
| https://huggingface.co/openbmb/MiniCPM5-1B |
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| MiniCPM4.1-8B |
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| Text reasoning, efficient inference, hybrid |
| reasoning, local reasoning apps |
| https://huggingface.co/openbmb/MiniCPM4.1-8B |
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| VoxCPM2 |
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| Text-to-speech, voice generation, creative voice |
| design, voice-enabled AI apps |
| https://huggingface.co/openbmb/VoxCPM2 |
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| #### Model Selection Guide |
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| If you want to build… Recommended Model |
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| Image understanding app: MiniCPM-V 4.6 |
| OCR / document assistant: MiniCPM-V 4.6 |
| Video understanding demo: MiniCPM-V 4.6 or MiniCPM-V 4.5 |
| Omni-modal assistant: MiniCPM-o 4.5 |
| Voice + vision interaction: MiniCPM-o 4.5 |
| Lightweight text assistant: MiniCPM5-1B |
| Local-first text app: MiniCPM5-1B |
| Text reasoning / problem-solving app: MiniCPM4.1-8B |
| Efficient local reasoning app: MiniCPM4.1-8B |
| TTS / voice generation app: VoxCPM2 |
| Creative voice experience: VoxCPM2 |
| Mobile / offline multimodal app: MiniCPM-V Apps + MiniCPM-V series |
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| #### Developer Support Documents |
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| MiniCPM-V / MiniCPM-o Cookbook — GitHub |
| Example projects, usage recipes, application ideas, and developer guides |
| https://github.com/OpenSQZ/MiniCPM-V-CookBook |
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| MiniCPM-V / MiniCPM-o Cookbook — Website |
| Web version of the cookbook; easier for participants to browse |
| https://opensqz.github.io/MiniCPM-V-CookBook/site/en/index.html |
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| MiniCPM-V Apps |
| Mobile app deployment examples and offline app resources |
| https://github.com/OpenBMB/ |
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| - Website: https://www.openbmb.cn/en/home |
| - Huggingface: https://huggingface.co/openbmb |
| - MiniCPM collection: https://huggingface.co/openbmb/collections |
| - GitHub: https://github.com/OpenBMB |
| - Twitter: https://x.com/OpenBMB |
| - Youtube tutorials: https://www.youtube.com/channel/UCyDtv4OTmeZ1OYrCHymYGow?utm_source=chatgpt.com\ |
| - Discord support: |
| - @zzhonglol2_50531 |
| - @tc_mb |
| - @yangzhizheng |
| |
| ### Black Forest Labs |
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| Models: FLUX.2 Klein base and distilled versions (available in 4B and 9B parameter sizes). Excellent for text-to-image generation and precise image editing workflows. |
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| - Website: |
| - huggingface: |
| - Twitter: |
| - Github: |
| - Docs: docs.bfl.ai |
| - Guide: hf.co/blog/black-forest-labs/flux-2-klein-lora |
| - Starter Space: hf.co/spaces/stephenbtl/klein-build-small-starter |
| - Model: FLUX.2-klein-base-4B • Apache 2.0 |
| - Trainer: github.com/ostris/ai-toolkit |
| - Discord support: @stephen.btl |
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| ### OpenAI Codex |
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| The powerful Codex coding agent (GPT-5.5) with built-in ecosystem plugins (GitHub, Figma, Hugging Face integrations), SSH connectivity to VMs, in-app UI browser checks, and the new automatic "Goal Mode" which can carry out multi-hour developer tasks unprompted. |
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| - Website: |
| - Codex docs: |
| - Huggingface: |
| - Twitter: |
| - Github: |
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| ### NVIDIA |
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| Models: Nemotron 3 Nano (30B total, 3B active MoE), Nemotron 3 Nano 4B (edge), Nemotron 3 Nano Omni (multimodal), Nemotron Cascade (math/code), Nemotron 3 ASR (speech recognition), Nemotron Parse (< 1B parameter document extraction), and Nemotron Embed VL (vision-language embeddings). |
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| - Website: |
| - Huggingface: |
| - Nemotron models: |
| - Twitter: |
| - Github: |
| - Nemotron 3 Nano usage guide: https://github.com/NVIDIA-NeMo/Nemotron/tree/main/use-case-examples/Simple%20Nemotron-3-Nano%20Usage%20Example |
| - Nemotron 3 Ultra: https://developer.nvidia.com/blog/nvidia-nemotron-3-ultra-powers-faster-more-efficient-reasoning-for-long-running-agents/ |
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| ### Modal |
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| Infrastructure for all AI workloads. |
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| #### inference |
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| Deploy and scale inference for LLMs, audio, image/video generation. |
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| #### training |
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| Fine-tune open-source models on single or multi-node clusters instantly. |
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| #### batch |
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| Parallelize massive jobs with Modal's hyper-elastic compute infrastructure. |
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| #### sandboxes |
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| Programmatically scale ephemeral environments for running untrusted code. |
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| Tools: Elastic, serverless compute infrastructure ideal for running fast inference, fine-tuning scripts in ~300 lines of code, parallel hyperparameter sweeps, and deploying coding agents within remote sandboxed environments. |
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| - Website: |
| - Docs: |
| - Huggingface: |
| - Twitter: |
| - Github: |
| - Discord support: @felicia_modal |
| - Slack: modal.com/slack |
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| ### JetBrains |
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| Models: Mellum 2 (12B parameter mixture of experts). Optimized for coding and high-throughput logic requests. Available in dedicated "Thinking" (reasoning-heavy) and "Instruct" (blazingly fast) configurations. |
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| What is Mellum2? |
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| • Family of open-source language models from JetBrains |
| • Built for coding and language tasks |
| • Optimized for low-latency, high-throughput inference |
| • Apache 2.0 licensed |
| • Deploy locally or in the cloud |
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| What can you build? |
| • Al coding assistants |
| • RAG applications |
| • Intelligent routing between models |
| • Code analysis and developer tools |
| • Real-time chat and automation |
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| - Website: |
| - Huggingface: |
| - Twitter: |
| - Github: |
| - GGUF Collection: https://huggingface.co/collections/JetBrains/mellum2-gguf |
| - Quickstart: https://huggingface.co/JetBrains/Mellum2-12B-A2.5B-Thinking-GGUF-Q4_K_M |
| - Discord support: |
| - @nikitapavlichenko |
| - @vano006503 |
| - @aral_dm |
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| ### Cohere Labs |
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| Cohere Transcribe is a 2B parameter fast ASR model covering 14 languages. The Aya 3.3B series (Base, Global, Earth, Fire, and Water variants) are tiny text generation models, each targeting and optimized for distinct geographical language families and low-resource languages. |
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| - cohere transcribe: https://huggingface.co/CohereLabs/cohere-transcribe-03-2026 |
| - tiny-aya-global: Best balance across languages and regions - https://huggingface.co/CohereLabs/tiny-aya-global-GGUF |
| - tiny-aya-water: European and Asia-Pacific languages - https://huggingface.co/CohereLabs/tiny-aya-water-GGUF |
| - tiny-aya-fire: South Asian languages - https://huggingface.co/CohereLabs/tiny-aya-fire-GGUF |
| - tiny-aya-earth: West Asian and African languages - https://huggingface.co/CohereLabs/tiny-aya-earth-GGUF |
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| Together, they are a good fit for local multilingual assistants, voice interfaces, accessibility tools, offline translation helpers, and small apps for real people. |
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| Resources |
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| - Cohere transcribe release blog: https://huggingface.co/blog/CohereLabs/cohere-transcribe-03-2026-release |
| - Tiny Aya example space: https://huggingface.co/spaces/ysharma/tiny-aya-build-small-sample |
| - Tiny Aya and Cohere transcribe full guide: https://huggingface.co/blog/CohereLabs/build-small-hackathon-with-cohere-models |
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| - Website: |
| - Huggingface: |
| - Twitter: |
| - Github: |
| - Discord support:\ |
| - @madeline_smith |
| - @alejandro_81346 |
| - @julianmack_43074 |
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