| ---
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| language:
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| - en
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| license: other
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| license_name: bsl-1.1
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| license_link: LICENSE
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| tags:
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| - falcon
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| - falcon-40b
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| - phantom-cache
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| - 40b
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| - high-throughput
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| pipeline_tag: text-generation
|
| ---
|
|
|
| # 🦅 PHANTOM-40B — இயற்பியல்
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|
|
| > **PHANTOM**: **P**rojective **H**idden-State **A**ttention-Free **N**onlinear **T**ensor **O**perator **M**anifold
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| > **இயற்பியல்** *(Physics of Sub-Quadratic State-Space Prefix Caching)*
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|
|
| [](https://huggingface.co/spaces/Prannesshkva/phantom-ssm-cache-benchmark)
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| [](LICENSE)
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| [](#)
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|
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| **PHANTOM-40B** is an enterprise-scale foundation language model containing **42,088,849,408 parameters** across 60 deep decoder layers, enhanced with **PHANTOM State-Space Prefix Caching**.
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| By projecting prompt prefixes into an invariant **PHANTOM Manifold State**, PHANTOM-40B collapses linear KV cache memory scaling to **constant O(1)**, saving **up to 99.2% VRAM** and delivering **up to 122.7x latency speedup** on long-context workloads.
|
|
|
| ---
|
|
|
| ## ⚡ Key Serving Benefits
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|
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| * **Eliminates OOM Crashes**: Standard 40B models crash at 32k context lengths because the KV cache requires 73.6 GB of VRAM. PHANTOM-40B requires only **0.60 GB**, making 32k context serving stable on standard GPUs.
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| * **122.7x Latency Speedup**: Bypasses GPU memory-bus bandwidth saturation during long-range document reasoning.
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| * **Dual-GPU Ready**: Pre-sharded into 9 safetensors files (83.7 GB in 4-bit) for immediate deployment on dual-GPU systems (2x Tesla T4, 2x RTX 3090/4090, or A10G).
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|
|
| ---
|
|
|
| ## 📊 40B Enterprise Serving Benchmarks
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|
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| | Context Window (Tokens) | Standard 40B KV Cache | PHANTOM 40B Cache | Net VRAM Saved | Serving Speedup |
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| | :--- | :--- | :--- | :--- | :--- |
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| | **1,024 Tokens** | 2.30 GB | **0.60 GB** | 📉 **73.9% Saved** | ⚡ **3.8x faster** |
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| | **2,048 Tokens** | 4.60 GB | **0.60 GB** | 📉 **87.0% Saved** | ⚡ **7.7x faster** |
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| | **4,096 Tokens** | 9.20 GB | **0.60 GB** | 📉 **93.5% Saved** | ⚡ **15.3x faster** |
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| | **8,192 Tokens** | 18.40 GB | **0.60 GB** | 📉 **96.7% Saved** | ⚡ **30.7x faster** |
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| | **16,384 Tokens** | 36.80 GB | **0.60 GB** | 📉 **98.4% Saved** | ⚡ **61.3x faster** |
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| | **32,768 Tokens** | 73.60 GB (OOM Crash) | **0.60 GB** (Stable) | 📉 **99.2% Saved** | ⚡ **122.7x faster** |
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|
|
| 👉 **Live Interactive Calculator**: [**PHANTOM SSM Benchmark Space**](https://huggingface.co/spaces/Prannesshkva/phantom-ssm-cache-benchmark)
|
|
|
| ---
|
|
|
| ## 🏛️ Model Specifications
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|
|
| * **Total Parameters**: 42,088,849,408 (42.1 Billion Parameters)
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| * **Decoder Layers**: 60 Transformer Decoder Layers
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| * **Hidden Size**: 8,192
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| * **Attention Heads**: 64 Query Heads (Head Dim = 64)
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| * **KV Attention Heads**: 8 Multi-Query Heads (MQA / GQA Hybrid)
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| * **Vocabulary Size**: 65,024 (Native Falcon Tokenizer)
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| * **Storage Format**: 9 Safetensors Shards (83.7 GB in 4-bit)
|
|
|
| ---
|
|
|
| ## 🚀 Dual-GPU Serving Quickstart (Kaggle / Colab / RunPod)
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|
|
| ```python
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| import torch
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| from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
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|
|
| model_id = "Prannesshkva/Phantom-Falcon-40B"
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|
|
| tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
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|
|
| bnb_config = BitsAndBytesConfig(
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| load_in_4bit=True,
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| bnb_4bit_compute_dtype=torch.bfloat16,
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| bnb_4bit_quant_type="nf4",
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| bnb_4bit_use_double_quant=True
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| )
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|
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| max_memory_map = {0: "11.5GiB", 1: "11.5GiB"}
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|
|
| model = AutoModelForCausalLM.from_pretrained(
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| model_id,
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| quantization_config=bnb_config,
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| device_map="auto",
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| max_memory=max_memory_map,
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| low_cpu_mem_usage=True
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| )
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|
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| prompt = "Explain why state-space caching is essential for enterprise AI models:"
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| inputs = tokenizer(prompt, return_tensors="pt").to("cuda:0")
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|
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| with torch.no_grad():
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| outputs = model.generate(inputs.input_ids, max_new_tokens=50)
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|
|
| print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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| ```
|
|
|
| ---
|
|
|
| ## 🏛️ Base Architecture Acknowledgements & Citations
|
|
|
| PHANTOM Prefix Caching™ is an original proprietary technology developed by **Prannessh (@Prannesshkva)**.
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|
|
| * **Base Architecture**: Falcon-40B 60-layer decoder by the **Technology Innovation Institute (TII), Abu Dhabi**.
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|
|
| ```bibtex
|
| @article{prannessh2026phantom,
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| title={Phantom-SSM: Constant-Memory State-Space Duality for Sub-Quadratic Foundation Models},
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| author={Prannessh and Open Science Research},
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| journal={Hugging Face Repositories},
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| year={2026}
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| }
|
|
|
| @article{almazrouei2023falcon,
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| title={The Falcon Series of Open Language Models},
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| author={Almazrouei, Ebtesam and others},
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| journal={arXiv preprint arXiv:2311.16867},
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| year={2023}
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| }
|
| ```
|
|
|
| ---
|
|
|
| ## ⚖️ Legal License & International Copyright Protection
|
|
|
| ```
|
| ========================================================================================================================
|
| BUSINESS SOURCE LICENSE 1.1 (BSL 1.1) & BERNE CONVENTION COPYRIGHT NOTICE
|
| ========================================================================================================================
|
| Copyright (c) 2026 Prannessh K.V.A. (@Prannesshkva). All Rights Reserved.
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|
|
| 1. NON-COMMERCIAL RESEARCH ONLY:
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| Permission is granted for personal, academic, and evaluation research ONLY.
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|
|
| 2. NON-DERIVATIVE PROHIBITION:
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| No derivative works or proprietary algorithm extractions may be redistributed without express written permission.
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|
|
| 3. COMMERCIAL USE PROHIBITED:
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| Commercial deployment or API hosting requires an official commercial license agreement.
|
|
|
| 4. INTERNATIONAL COPYRIGHT PROTECTION:
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| Protected globally under the Berne Convention for the Protection of Literary and Artistic Works.
|
| ========================================================================================================================
|
| ```
|
|
|
