--- library_name: mlx license: other license_name: qwen-community-1.0 license_link: LICENSE base_model: Qwen/Qwen3.8-Flash-Next pipeline_tag: image-text-to-text tags: - mlx - quantized - qwen4-exp --- # Qwen3.8-Flash-Next MLX Activation-Weighted 3-bit This is a reproducible MLX conversion of [`Qwen/Qwen3.8-Flash-Next`](https://huggingface.co/Qwen/Qwen3.8-Flash-Next) at immutable revision `f5d08274bafd880402bd16f5e3e6c514136ec06c`. The 48 base routed-expert banks use fresh MLX affine Q3/group-64 codes generated directly from the original BF16 checkpoint. Their scales and biases are refit against frozen image-and-text expert-input second moments. Remaining eligible core, MTP, and vision matrices stay Q4; the 160-wide n-gram table stays Q4/group-32. - Artifact payload: 83.49 GiB - Quantized Q2 modules: 0 - Quantized Q3/group-64 modules: 144 - Quantized Q4/group-32 modules: 128 - Quantized Q4/group-64 modules: 783 - Source: 180B parameters including 125B main, 51B n-gram embedding, and 4B MTP - Native context: 262,144 tokens ## Run locally with mere.run This profile requires the managed model update after mere.run v0.45.0. With a build that contains that update, review the license and pull the checkpoint: ```bash mere.run model pull vision-chat-q38-flash-next-3bit \ --accept-license-terms ``` The repository is public and ungated. The acceptance option records your acknowledgment of the bundled Qwen Community License 1.0. To generate text with the bundled multi-token prediction (MTP) head, run: ```bash mere.run text chat \ --model vision-chat-q38-flash-next-3bit \ --context-size 32768 \ --max-tokens 256 \ --temperature 0 \ --no-thinking \ --stream \ --stats \ --prompt "Explain sparse attention in three short sentences." ``` For an external SSD, add `--cache-dir /Volumes/Models/huggingface-cache` to the pull command and replace the sample path with your mounted volume. Keep the volume mounted when you use the model. ## Native qualification The fresh Q3 checkpoint passed a no-regression comparison against the pinned published Q4 checkpoint in mere.run on a 128 GiB Apple Silicon Mac. MTP was disabled during checkpoint selection. - The candidate passed 58 of 61 cases by exact expected output. - The three absolute misses matched the published Q4 output exactly. - The sealed holdout produced identical candidate and Q4 outputs in all 16 cases, including exact output on all eight image and OCR cases. - The holdout peak memory footprint was 62,065,713,472 bytes for this profile and 77,180,432,496 bytes for Q4, a 19.58% reduction. Neither run increased swap usage. The bounded suites don't establish general model quality or BF16 parity. For the test identities, hashes, memory measurements, and limits, see `MERERUN_QUALIFICATION.json`. ## Runtime status The tensor inventory, source hashes, MLX packing, fused-expert split, convolution layout, and zero-centered RMSNorm conversion are validated by the bundled `MERERUN_CONVERSION.json`. Use a Qwen4Exp-aware runtime such as mere.run or mlx-vlm. ## License This redistribution retains the upstream **Qwen Community License 1.0** in `LICENSE`. Review it before use. In particular, it contains attribution/display requirements for very large commercial products and separate-license conditions for certain commercial Model-as-a-Service and AI Work Assistant uses. The model is not gated; downloading or using it does not remove those terms. The upstream model card is preserved as `README.upstream.md`.