Experimental Release: Pending Further Verification / Empirical Validation
This checkpoint represents an active research artifact from DuoNeural's statistical mechanics quantization program. All empirical benchmarks and physics proofs are documented transparently below.
Developed by
Jesse Caldwell, Archon, and Aura ✨ (DuoNeural Research Lab)
.
Python Algorithmic AST Execution (20 Unit Tests):
85.0% (17/20)
Inference Decode Throughput:
138.1 t/s
on NVIDIA GeForce RTX 4080 Super (32GB VRAM)
Empirical Benchmark Performance
Evaluation Arm
Codebook
Footprint
Perplexity (131k tokens)
GSM8K Math Acc
Python Code AST (20 Tests)
Hermes Tool Calling
Decode Speed
Base BF16 Control
BF16
14.19 GiB
2.8039
25/25 (100.0%)
20/20 (100.0%)
15/15 (100.0%)
43.3 t/s
Coder7B Naive IQ3_XXS
IQ3_XXS (~3.2 bpw)
2.90 GiB
2.8301
25/25 (100.0%)
17/20 (85.0%)
15/15 (100.0%)
138.0 t/s
Coder7B G-TAP v3 IQ3_XXS
IQ3_XXS (~3.2 bpw)
2.90 GiB
2.8264
23/25 (92.0%)
17/20 (85.0%)
15/15 (100.0%)
138.8 t/s
Coder7B G-TAP v3 Q4_K_M
Q4_K_M (~4.5 bpw)
4.36 GiB
2.8209
25/25 (100.0%)
16/20 (80.0%)
14/15 (93.3%)
109.1 t/s
Algorithmic AST Stability at 2.90 GiB
Standard PTQ quantization triggers a severe syntax collapse cliff on specialized coding models below 4 bits. By combining our 131,072-token code-infused activation Hessian with G-TAP v3 Onsager cavity damping, this sub-3.5-bit checkpoint successfully executes complex algorithmic unit tests:
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