Qwen3.8-Flash-Next MLX Activation-Weighted 3-bit
This is a reproducible MLX conversion of
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:
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:
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.