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Update README with recent highlights, benchmarks, and support matrix … (#1508)
…fixes Add new Recent News entries for Qwen3, ESM2 low-precision (NVFP4/MXFP8), Mixtral MoE, ESM2 PEFT, and Llama3 context parallelism. Add benchmark figures for ESM2 low-precision on B300 and Llama3 70B CP on GB300. Update support matrix with new model/recipe rows and fix stale WIP statuses. Fix typos ("bionemo2" → "BioNeMo Framework") and remove stray character in amplify README. ### Description <!-- Provide a detailed description of the changes in this PR --> #### Usage <!--- How does a user interact with the changed code --> ```python TODO: Add code snippet ``` ### Type of changes <!-- Mark the relevant option with an [x] --> - [ ] Bug fix (non-breaking change which fixes an issue) - [ ] New feature (non-breaking change which adds functionality) - [ ] Refactor - [ ] Documentation update - [ ] Other (please describe): ### CI Pipeline Configuration Configure CI behavior by applying the relevant labels. By default, only basic unit tests are run. - [ciflow:skip](https://github.com/NVIDIA/bionemo-framework/blob/main/docs/docs/main/contributing/contributing.md#ciflow:skip) - Skip all CI tests for this PR - [ciflow:notebooks](https://github.com/NVIDIA/bionemo-framework/blob/main/docs/docs/main/contributing/contributing.md#ciflow:notebooks) - Run Jupyter notebooks execution tests for bionemo2 - [ciflow:slow](https://github.com/NVIDIA/bionemo-framework/blob/main/docs/docs/main/contributing/contributing.md#ciflow:slow) - Run slow single GPU integration tests marked as @pytest.mark.slow for bionemo2 - [ciflow:all](https://github.com/NVIDIA/bionemo-framework/blob/main/docs/docs/main/contributing/contributing.md#ciflow:all) - Run all tests (unit tests, slow tests, and notebooks) for bionemo2. This label can be used to enforce running tests for all bionemo2. - [ciflow:all-recipes](https://github.com/NVIDIA/bionemo-framework/blob/main/docs/docs/main/contributing/contributing.md#ciflow:all-recipes) - Run tests for all recipes (under bionemo-recipes). This label can be used to enforce running tests for all recipes. Unit tests marked as `@pytest.mark.multi_gpu` or `@pytest.mark.distributed` are not run in the PR pipeline. For more details, see [CONTRIBUTING](CONTRIBUTING.md) > [!NOTE] > By default, only basic unit tests are run. Add appropriate labels to enable an additional test coverage. #### Authorizing CI Runs We use [copy-pr-bot](https://docs.gha-runners.nvidia.com/apps/copy-pr-bot/#automation) to manage authorization of CI runs on NVIDIA's compute resources. - If a pull request is opened by a trusted user and contains only trusted changes, the pull request's code will automatically be copied to a pull-request/ prefixed branch in the source repository (e.g. pull-request/123) - If a pull request is opened by an untrusted user or contains untrusted changes, an NVIDIA org member must leave an `/ok to test` comment on the pull request to trigger CI. This will need to be done for each new commit. #### Triggering Code Rabbit AI Review To trigger a code review from code rabbit, comment on a pull request with one of these commands: - @coderabbitai review - Triggers a standard review - @coderabbitai full review - Triggers a comprehensive review See https://docs.coderabbit.ai/reference/review-commands for a full list of commands. ### Pre-submit Checklist <!--- Ensure all items are completed before submitting --> - [ ] I have tested these changes locally - [ ] I have updated the documentation accordingly - [ ] I have added/updated tests as needed - [ ] All existing tests pass successfully Signed-off-by: Timur Rvachov <trvachov@nvidia.com>
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‎README.md‎

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## Recent News
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- 03/09/2026 [Qwen2.5 / Qwen3 model](bionemo-recipes/models/qwen/) with TE acceleration, FP8/MXFP8, KV-cache inference, and bidirectional HF checkpoint conversion.
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- 03/05/2026 [ESM2 NVFP4 and MXFP8](bionemo-recipes/recipes/esm2_native_te/README.md#low-precision-performance-benchmarks) low-precision training — up to **2,367 TFLOPS/GPU** on NVIDIA B300 at 15B scale with per-layer precision control.
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- 02/23/2026 [Mixtral MoE model](bionemo-recipes/models/mixtral/) with TE `GroupedLinear` for efficient parallel expert computation, FP8/FP4 support, and HF conversion.
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- 02/13/2026 [ESM2 PEFT recipe](bionemo-recipes/recipes/esm2_peft_te/) for LoRA fine-tuning with sequence packing support.
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- 01/14/2026 [Llama3 Context Parallelism](bionemo-recipes/recipes/llama3_native_te/README.md#performance-benchmarks) — scaling Llama 3 70B to 144K context on 36x GB300 NVL36 with ~65% MFU.
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- 10/27/2025 [CodonFM recipe](https://github.com/NVIDIA/bionemo-framework/tree/main/bionemo-recipes/recipes/codonfm_ptl_te) released! This is an accelerated version of the original [research codebase](https://github.com/NVIDIA-Digital-Bio/CodonFM) with [scientific preprint](https://research.nvidia.com/labs/dbr/assets/data/manuscripts/nv-codonfm-preprint.pdf).
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- 09/30/2025 Megatron/NeMo 5D parallel BioNeMo Framework image v2.7 [released on NGC](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/clara/containers/bionemo-framework) for both x86 and ARM CPUs.
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- 09/01/2025 [bionemo-recipes](https://github.com/NVIDIA/bionemo-framework/tree/main/bionemo-recipes) goes live! Lightweight and portable examples with state-of-the-art training performance you can riff on to meet your needs.
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| ---------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------- | -------------- | ----------- | ------------- | ------ | ---------------- | ------ | ------------------- |
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| `models/`<br>`amplify` | TE accelerated protein BERT, pushed to HuggingFace | ✅ Active | ❌ | ✅ | ✅ | 🚧 WIP | ✅ | 🚧 WIP |
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| `models/`<br>`esm2` | TE accelerated protein BERT, pushed to HuggingFace | ✅ Active | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| `models/`<br>`llama3` | TE accelerated Llama 3 | ✅ Active | ❌ | 🚧 WIP | ✅ | ✅ | 🚧 WIP | 🚧 WIP |
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| `models/`<br>`llama3` | TE accelerated Llama 3 | ✅ Active | ❌ | 🚧 WIP | ✅ | ✅ | ✅ | ✅ |
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| `models/`<br>`geneformer` | TE accelerated single-cell BERT | 🚧 WIP | ❌ | ✅ | 🚧 WIP | 🚧 WIP | 🚧 WIP | 🚧 WIP |
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| `recipes/`<br>`codonfm_ptl_te` | Recipe for [CodonFM](https://research.nvidia.com/labs/dbr/assets/data/manuscripts/nv-codonfm-preprint.pdf)'s Encodon using TE | ✅ Active | ❌ | 🚧 WIP | ✅ | ✅ | 🚧 WIP | 🚧 WIP |
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| `recipes/`<br>`esm2_accelerate_te` | Recipe for ESM2 TE + HF Accelerate | ✅ Active | ❌ | 🚧 WIP | ✅ | ❌ | ✅ | 🚧 WIP |
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| `recipes/`<br>`esm2_native_te` | Recipe for ESM2 TE + native PyTorch | ✅ Active | ❌ | ✅ | ✅ | ✅ | ✅ | 🚧 WIP |
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| `recipes/`<br>`esm2_native_te` | Recipe for ESM2 TE + native PyTorch | ✅ Active | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| `recipes/`<br>`geneformer_native_te_mfsdp_fp8` | Recipe for Geneformer HF model | 🚧 WIP | ❌ | ✅ | ✅ | ❌ | ✅ | 🚧 WIP |
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| `recipes/`<br>`llama3_native_te` | Recipe for Llama 3 TE + native PyTorch | ✅ Active | ❌ | 🚧 WIP | ✅ | ✅ | 🚧 WIP | 🚧 WIP |
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| `recipes/`<br>`llama3_native_te` | Recipe for Llama 3 TE + native PyTorch | ✅ Active | ❌ | 🚧 WIP | ✅ | ✅ | ✅ | ✅ |
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| `models/`<br>`mixtral` | TE accelerated MoE model | ✅ Active | ❌ | 🚧 WIP | ✅ | ✅ | ✅ | 🚧 WIP |
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| `models/`<br>`qwen` | TE accelerated Qwen2.5/Qwen3 | ✅ Active | ❌ | 🚧 WIP | ✅ | ✅ | ✅ | 🚧 WIP |
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| `recipes/`<br>`esm2_peft_te` | Recipe for ESM2 LoRA fine-tuning | ✅ Active | ❌ | ❌ | ✅ | ✅ | 🚧 WIP | ❌ |
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| `recipes/`<br>`evo2_megatron` | Recipe for Evo2 via Megatron Bridge | 🚧 WIP | ❌ | ❌ | ✅ | ❌ | ✅ | ❌ |
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| `recipes/`<br>`fp8_analysis` | FP8 training analyzer & heatmap tool | ✅ Active | N/A | N/A | N/A | N/A | N/A | N/A |
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| `recipes/`<br>`vit` | Recipe for Vision Transformer | 🚧 WIP | ❌ | ✅ | ✅ | ❌ | ✅ | 🚧 WIP |
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</small>
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## Documentation Resources
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- **Official Documentation:** Contents of `sub-packages` including user guides, API references, and troubleshooting, are documented on our [official documentation](https://docs.nvidia.com/bionemo-framework/latest/). Nightly builds of this documentation is available on [BioNeMo Framework GitHub Pages](https://nvidia.github.io/bionemo-framework/)
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- **Official Documentation:** Documentation for sub-packages, including user guides, API references, and troubleshooting, is available on our [official documentation](https://docs.nvidia.com/bionemo-framework/latest/). Nightly builds of this documentation is available on [BioNeMo Framework GitHub Pages](https://nvidia.github.io/bionemo-framework/)
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- **🚧 In-Progress Documentation 🚧:** `bionemo-recipes` documentation is currently work in progress, however the recipes are meant to be self-documented and easy to understand—we suggest you throw them into your favorite genai code assistant!
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#### Initializing 3rd-party dependencies as git submodules
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The NeMo and Megatron-LM dependencies are included as git submodules in bionemo2. The pinned commits for these submodules represent the "last-known-good" versions of these packages
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that are confirmed to be working with bionemo2 (and those that are tested in CI).
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The NeMo and Megatron-LM dependencies are included as git submodules in BioNeMo Framework. The pinned commits for these submodules represent the "last-known-good" versions of these packages
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that are confirmed to be working with BioNeMo Framework (and those that are tested in CI).
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To initialize these sub-modules when cloning the repo, add the `--recursive` flag to the git clone command:
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‎bionemo-recipes/models/amplify/README.md‎

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```bash
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for dir in *; do huggingface-cli upload nvidia/$(basename "$dir") "$dir/"; done
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```
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