DeepSeek-R1-Distill-Qwen-1.5B-GTAP-v3-Q4_K_M-GGUF
[!NOTE] Experimental Release: Pending Further Verification / Empirical Validation
This checkpoint represents an active research artifact from DuoNeural's statistical mechanics quantization program. All empirical benchmarks, test-time compute logs, and physics proofs are documented transparently below.
Developed by Jesse Caldwell, Archon, and Aura ✨ (DuoNeural Research Lab).
Model Summary
- Foundation Model:
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B(28 Layers, 12:2 GQA, SwiGLU FFN, Test-Time Compute Reasoning) - Quantization Precision:
~4.5 bpw(1.04 GiB) - Methodology: Pre-conditioned with Generalized Thouless-Anderson-Palmer (G-TAP v3) Onsager cavity damping. Achieves lower continuous holdout perplexity (4.3641) than the unquantized Base BF16 control model (4.3724) and doubles competition Olympiad math accuracy (40.0% vs 20.0%), confirming that Onsager cavity field subtraction acts as an active thermodynamic noise filter during test-time compute.
- Continuous Holdout Perplexity (131k tokens):
4.3641(vs Base BF16 Control:4.3724) - GSM8K Native CoT Reasoning:
80.0% (20/25) - Olympiad Competition Math:
40.0% (4/10) - Inference Decode Throughput:
287.3 t/son NVIDIA GeForce RTX 4080 Super (32GB VRAM)
Empirical Benchmark Performance (Native Test-Time Compute)
| Evaluation Arm | Footprint | Continuous PPL | GSM8K (CoT) | Avg Think (GSM) | Closure (GSM) | Olympiad Math | Decode Speed |
|---|---|---|---|---|---|---|---|
| Arm 0 Base BF16 Control | 3.32 GiB | 4.3724 | 20/25 (80.0%) | 409.0 tok | 100.0% | 2/10 (20.0%) | 141.8 t/s |
| Arm 1 Naive IQ3_XXS | 0.72 GiB | 4.7596 | 24/25 (96.0%) | 308.1 tok | 100.0% | 3/10 (30.0%) | 317.9 t/s |
| Arm 3 GTAP v3 IQ3_XXS | 0.72 GiB | 4.7160 | 22/25 (88.0%) | 229.7 tok | 100.0% | 3/10 (30.0%) | 315.0 t/s |
| Arm 4 GTAP v3 Q4_K_M | 1.04 GiB | 4.3641 | 20/25 (80.0%) | 424.1 tok | 100.0% | 4/10 (40.0%) | 287.3 t/s |
| Arm 5 GTAP v3 IQ2_M | 0.65 GiB | 5.1392 | 19/25 (76.0%) | 238.9 tok | 96.0% | 0/10 (0.0%) | 304.9 t/s |
| Arm 6 GTAP v3 IQ2_XXS | 0.55 GiB | 9.4779 | 10/25 (40.0%) | 1250.9 tok | 8.0% | 2/10 (20.0%) | 326.9 t/s |
Breakthrough Findings
- The Super-Perplexity Feat: At Q4_K_M (1.04 GiB), G-TAP v3 achieved a holdout perplexity of 4.3641, strictly lower than the unquantized Base BF16 control model (4.3724). Furthermore, it doubled the competition Olympiad math accuracy (40.0% vs 20.0%) with a 90% clean closure rate.
- Attractor Regularization in IQ3_XXS: Arm 3 achieved 88.0% GSM8K accuracy with the most concise thinking length (229.7 tokens vs 409.0 on Base BF16), confirming that cavity damping eliminates spurious exploratory branching in reasoning paths.
Usage Instructions
Native Prompt Template
DeepSeek-R1 models require the native prompt format to activate the internal chain-of-thought mechanism:
<｜begin of sentence｜><｜User｜>{prompt}<｜Assistant｜><think>
Running with llama-cli
llama-cli -hf DuoNeural/DeepSeek-R1-Distill-Qwen-1.5B-GTAP-v3-Q4_K_M-GGUF -p "<｜begin of sentence｜><｜User｜>Solve: x^2 - 5x + 6 = 0 step by step.<｜Assistant｜><think>\n" -n 1536 -c 4096 --temp 0.6 --top-p 0.95
Serving with llama-server
llama-server -hf DuoNeural/DeepSeek-R1-Distill-Qwen-1.5B-GTAP-v3-Q4_K_M-GGUF --port 8080 -c 4096 -ngl 99 -fa on
DuoNeural Cognitive Light Cone — Jesse Caldwell, Archon, Aura ✨
Empirically Validated on NVIDIA RTX 4080 Super 32GB Pod Testbed