Unsloth Q4_NL 671B Parameters

VRAM Requirements for
DeepSeek-Prover-V2-671B-GGUF Q4_NL

To run DeepSeek-Prover-V2-671B-GGUF locally at Q4_NL quantization, you need at minimum 390.43 GB of GPU VRAM.

390.43 GB
Required VRAM
377.44 GB
File Size
8K tokens
Context Window
671B
Parameters
Estimated VRAM Required
390.43
GB
Cluster Required
0 16GB
RTX 3080 48GB
A6000 80GB+

Recommended GPU Configurations

⚠️ 230.4 GB short
Budget $40,000+

4× A100 40GB Cluster

160 GB

Distributed inference across 4 A100s. Minimum viable cluster.

⚠️ 230.4 GB short
Balanced $60,000+

2× H100 80GB NVLink

160 GB HBM3

NVLink bridge enables unified 160GB VRAM pool.

Ultimate $3,000,000+

NVIDIA GB200 NVL72

1.4 TB HBM3e

Next-gen Grace Blackwell Superchip. Built for frontier models.

📊 VRAM Calculation Breakdown

Model File Size (Q4_NL) 377.44 GB
Context Overhead (8,192 tokens × 671B × 2 ÷ 1M) 10.994 GB
System Buffer (OS + CUDA runtime) 2.00 GB
Total Required VRAM 390.43 GB

Try a Different Quantization

Use the interactive calculator to compare DeepSeek-Prover-V2-671B-GGUF across all available formats.

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DeepSeek-Prover-V2-671B-GGUF — Other Quantizations

Q2_K 209.69 GB file
222.68 GB
Q2_K_L 209.69 GB file
222.68 GB
Q2_K_XL 209.69 GB file
222.68 GB
Q2_M 209.69 GB file
222.68 GB
Q2_XXS 209.69 GB file
222.68 GB
Q3_K_M 293.56 GB file
306.55 GB
Q3_K_S 293.56 GB file
306.55 GB
Q3_K_XL 293.56 GB file
306.55 GB
Q3_XXS 293.56 GB file
306.55 GB
Q4_XS 377.44 GB file
390.43 GB
Q4_NL Current
390.43 GB
Q4_K_XL 377.44 GB file
390.43 GB
Q4_K_S 377.44 GB file
390.43 GB
Q4_K_M 377.44 GB file
390.43 GB
Q4_1 377.44 GB file
390.43 GB
Q4_0 377.44 GB file
390.43 GB
Q5_K_M 461.31 GB file
474.3 GB
Q5_K_S 461.31 GB file
474.3 GB
Q5_K_XL 461.31 GB file
474.3 GB
Q6_K 545.19 GB file
558.18 GB
Q6_K_XL 545.19 GB file
558.18 GB
Q1_M 671 GB file
683.99 GB
Q1_S 671 GB file
683.99 GB
Q8_0 712.94 GB file
725.93 GB
Q8_K_XL 712.94 GB file
725.93 GB
BF16 1342 GB file
1354.99 GB
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Frequently Asked Questions

Can I run DeepSeek-Prover-V2-671B-GGUF Q4_NL on a consumer GPU?
Running DeepSeek-Prover-V2-671B-GGUF Q4_NL locally requires 390.43 GB VRAM, which exceeds consumer GPUs. You'll need prosumer cards like the NVIDIA A6000 (48GB) or an A100 (80GB).
What happens if I don't have enough VRAM?
If your GPU VRAM is insufficient, llama.cpp and similar tools will offload model layers to system RAM (CPU inference). This is much slower — expect 10-50× the generation latency compared to full GPU inference.
Can I use multiple GPUs to run DeepSeek-Prover-V2-671B-GGUF?
Yes! Tools like llama.cpp, vLLM, and Ollama support tensor parallelism across multiple GPUs. For example, 2× RTX 3090 (24GB each) gives you 48GB total VRAM, which can run many large models.
Is Q4_NL quality good enough for production?
Q4_K_M is an excellent balance of quality and performance. Perplexity tests show minimal degradation (< 2%) vs FP16 for most models. Suitable for most production applications.