GLM-5.3-Flash-AFM-MLX-4bit

[!WARNING] Experimental AFM artifact. This checkpoint targets AFM and AFMKit v0.1.18-rc.3 or newer. It may not work with other MLX runtimes or older AFM releases. Behavior, quality, performance, memory use, compatibility, and file layout may change.

GLM-5.3-Flash AFM MLX 4-bit MTP

This is an AFM format-v3 conversion of the official zai-org/GLM-5.3-Flash checkpoint at revision 04c4e9e95c5da8862dced7e5056455116f83a7e0. It is converted directly from the official FP8 SafeTensors distribution; it is not a re-quantization of a third-party 4-bit checkpoint.

The conversion contains 201 weight files totaling 181,694,111,440 bytes (approximately 169.2 GiB), excluding runtime memory and KV cache. Loading the checkpoint measured approximately 169.4 GB wired memory on a 512 GB Apple Silicon development machine. A smaller minimum memory configuration has not been established.

Conversion

• AFM conversion format: 3
• Profile: mlx-affine-4
• Quantization: affine 4-bit, group size 64
• Source MTP layer: preserved
• num_nextn_predict_layers: 1
• Conversion units completed: 201/201
• Mapped tensors: 3,059
• Source tensors omitted from the NextN layer: 0
• Routed experts are reconstructed in numerical expert order.
• Router weights remain FP32.
• Attention projection layout transformations are applied for the AFM GLM runtime.
• Vision weights, tokenizer, processor assets, and the upstream chat template are preserved.
• Detailed source, shard, size, and SHA-256 provenance is recorded in .afm-mlx-conversion.json.

End-to-end vision quality is not qualified. Weight preservation alone is not an image-quality parity claim.

MTP status

The structural layer 45 NextN tensors are present and converted. This is different from a general quality or speedup claim.

Qualification with AFMKit v0.1.18-rc.3 succeeded:

• The server loaded GLM embedded NextN layer at depth 1.
• An explicit greedy streaming request returned exactly PASS with finish_reason=stop.
• The diagnostic profile recorded draftedTokens=4, acceptedTokens=4, headForwards=9, targetForwards=5, and zero rejection replays.
• All 201 tensor files matched their recorded sizes and SHA-256 digests before upload.
• Hugging Face verified all 212 published files after upload.

This is runtime and integrity qualification, not a standard benchmark result. Throughput and correctness under other prompts, batch sizes, cache states, tool calls, and vision inputs remain unmeasured.

Run with AFM

Use AFM built against AFMKit v0.1.18-rc.3 or newer:

afm mlx -m scouzi1966/GLM-5.3-Flash-AFM-MLX-4bit \
  --mtp --reasoning-effort low --port 9999

The GLM-5.3 template does not expose a direct thinking off switch. Low reasoning effort reduces but does not eliminate reasoning output.

curl http://127.0.0.1:9999/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "scouzi1966/GLM-5.3-Flash-AFM-MLX-4bit",
    "messages": [{"role": "user", "content": "Return exactly PASS and nothing else."}],
    "temperature": 0,
    "max_tokens": 128,
    "stream": true
  }'

Attribution and license

Original model by Z.AI. The original MIT license is included in LICENSE. The upstream model card is preserved in UPSTREAM_README.md; upstream model claims are not measurements of this conversion. AFM conversion and packaging are provided by the AFM / AFMKit project.