Instructions to use Yanun/MiMo-V2.6-Flash-RL-MXFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Yanun/MiMo-V2.6-Flash-RL-MXFP4 with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("Yanun/MiMo-V2.6-Flash-RL-MXFP4") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use Yanun/MiMo-V2.6-Flash-RL-MXFP4 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "Yanun/MiMo-V2.6-Flash-RL-MXFP4" --prompt "Once upon a time"
- Atomic Chat
MiMo-V2.6-Flash-RL β complete Whallm installed artifact
Complete artifact uploaded and remote integrity checked. A usable revision
must contain manifest.json and every file listed in its files array, with
matching sizes and SHA-256 values. Whallm must pin a verified immutable revision,
not the mutable main branch.
This is a prepared installed model for Whallm on Apple Silicon, not a standard Transformers or mlx-lm checkpoint. Downloading a verified complete revision requires no local weight conversion.
Source and preservation
Source: XiaomiMiMo/MiMo-V2.6-Flash-RL,
revision 5711b268169967567844e1e560e8a3966da959b1.
The source model card declares MIT licensing. Original code, notices and
model documentation are preserved under checkpoint/.
All 90 upstream files are retained whole or reconstructible byte-for-byte. The 64 repacked source shards passed reconstruction against their original SHA-256 values. The other 26 files were preserved whole, including:
- AudioTokenizer, original three-layer MTP, five-layer DFlash and mask embedding;
- all tokenizer, processor and model configuration files;
- original model code, model card, technical report and architecture image.
All vision and audio-patch tensors are preserved. Original common FP8 weights
and scales are retained in checkpoint/common.bin; no encoder or draft weights
were discarded to produce a text-only subset.
Installed layout
Format 4 contains 151 payload files / 193,730,445,975 bytes (180.426 GiB),
excluding manifest.json and this model card.
experts/: 12,032 native MXFP4 experts, 47 expert-bearing layers, 256 experts per layer, top-8 routing. Each packed expert is 13,369,344 bytes. Values were repacked, not requantized.common.bin: 331 prepared target-backbone tensors (48 backbone/KV layers).vision/common.bin: 364 prepared vision tensors.audio/common.bin: 95 prepared audio-patch tensors.mtp/common.bin: 36 prepared MTP tensors.checkpoint/: preserved original common payload, exact shard headers, and all companion files.checkpoint-map.json: original file provenance and tensor-byte reconstruction map.preservation.json: completed local source-preservation checks.
Common FP8 tensors are decoded to BF16. Fused QKV is decoded with the source TP=4 shard-local scale grids and reordered into canonical Q/K/V. Original FP8 bytes and scales remain available for lossless source reconstruction. This is not a claim of bitwise parity with SGLang's subsequent CUDA FP8 requantization.
Validation and limitations
The complete target backbone loaded locally and generated Hello. and δ½ ε₯½γ.
Generation resumed successfully after closing an active generation iterator.
Local source preservation and all installed-file SHA-256 values were verified.
Complete data preservation does not mean complete runtime support. Vision, video and audio processing, encoder execution, MTP/DFlash decoding, document integration, and MCP remain unfinished in the development implementation. Tool/API and App end-to-end acceptance are not complete. Short text smoke tests are not full-model reference parity, quality benchmarks or speed measurements. The checkpoint's 1,048,576-token limit is not a locally validated usable context.
This model upload is not an App release. Use a Whallm build that explicitly
supports mimo-v2.6-flash-rl / manifest format 4. Preserve the complete manifest
file set; do not delete currently unused modalities or draft models.
Publication verification
All 151 payload files and the manifest were checked against the local artifact. LFS SHA-256 values and sizes match; Git-stored files and the manifest were downloaded anonymously and SHA-256 checked at an immutable commit. This does not claim a second full download of all 180.426 GiB or App end-to-end acceptance.
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XiaomiMiMo/MiMo-V2.6-Flash-RL