Agnes-3.0-Flash — MLX oQ4e + MTP
oQ4e (mixed-precision) MLX quantization of Agnes-AI/Agnes-3.0-Flash (Apache-2.0), grafted with Qwen3.8's vision tower and Agnes's native MTP head.
- oQ4e mixed-precision quantization — sensitive layers kept at higher precision, rest at 4-bit
- ~19 GB across 5 shards
- 262,144-token context, thinking on/off via the original chat template
- MTP head grafted: Agnes native MTP head with FFN padded 17408→19456 (zero-pad, mathematically identical), quantized to 4-bit
- Vision tower grafted from Qwen3.8 (333 bf16 tensors, byte-identical to Agnes original)
Architecture
Agnes-3.0-Flash is a 33B hybrid attention model:
- 54 recurrent (Gated DeltaNet) layers + 18 global attention layers
- GQA 6:1 (24q/4kv heads, dim 256), 3-axis RoPE, causal conv kernel 4
- Hidden size 5120, intermediate size 17408 (Agnes native)
- MTP head intermediate size 19456 (Qwen3.8 compatible, padded from 17408)
What changed
Converted from the original Agnes format to standard Qwen3.5 architecture:
- Folded parallel FFN into main MLP via concatenation (intermediate_size: 19456)
- Renamed
delta_attn→linear_attn,global_attn→self_attn - Converted one-centered RMSNorm to standard format
- Cast bf16 → fp16 for serialization compatibility
MTP graft:
- Padded Agnes native MTP head FFN layers (gate_proj, up_proj: +2048 rows; down_proj: +2048 cols) to match Qwen3.8's expected 19456
- Quantized MTP weights to 4-bit affine (group_size=64)
- Grafted 333 vision tensors from Qwen3.8 (byte-identical to Agnes original)
Benchmark
Measured on M3 Max 64GB, oMLX, temperature 0:
| Metric | Baseline (no MTP) | With MTP | Speedup |
|---|---|---|---|
| Throughput | 15.0 tok/s | 21.7 tok/s | 1.44× |
| Acceptance rate | — | 85.7% | — |
| Tokens per cycle | — | 2.46 | — |
Usage
Place under ~/.omlx/models/hermitdave/ and enable mtp_enabled + vlm_mtp_enabled in model settings.
Attribution
- Original model: Agnes-AI
- Vision tower: Qwen3.8-27B (byte-identical)
- Converted with Hermes Agent + mlx_lm
- Quantized with oMLX