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DeepSeek Coder V2 16B

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920.2KDownloads600LikesJun 2024Veröffentlicht131K TokenKontextDeepSeekLizenz68 GutQualität

DeepSeek Coder V2 16B (16B parameters) requires approximately 14.9 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 2.4000000953674316B active parameters, it uses less memory than its total parameter count suggests. For the best balance of quality and speed, we recommend hardware with at least 18 GB of VRAM.

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Copy-paste commands to run DeepSeek Coder V2 16B on your machine.

Run

lms load DeepSeek-Coder-V2-Lite-Instruct && lms server start

Quick specs

Parameters16B (2.4B active)
Architecturemoe (MoE)
Context131K tokens
Modalitytext
Min RAM6.2 GB
Rec. RAM9.8 GB (Q4_K_M)
LicenseDeepSeek
FamilyDeepSeek
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About this model

We present DeepSeek-Coder-V2, an open-source Mixture-of-Experts (MoE) code language model that achieves performance comparable to GPT4-Turbo in code-specific tasks. Specifically, DeepSeek-Coder-V2 is further pre-trained from an intermediate checkpoint of DeepSeek-V2 with additional 6 trillion tokens. Through this continued pre-training, DeepSeek-Coder-V2 substantially enhances the coding and mathematical reasoning capabilities of DeepSeek-V2, while maintaining comparable performance in general language tasks.

Verwandte Modelle

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Quantisierungsoptionen

VRAM-Schätzungen nach Quantisierungsstufe

No hardware detected — fit column shows raw VRAM estimates

QuantBitsVRAMQualityFit
Q2_K
2
6.2 GB
Low
Q3_K_S
3
7.8 GB
Low
NVFP4
4
9.0 GB
Medium
Q4_K_M
4
9.8 GB
Medium
Q5_K_M
5
11.5 GB
High
Q6_K
6
13.1 GB
High
Q8_0
8
17.1 GB
Very High
F16
16
32.8 GB
Maximum

Quality benchmarks

DeepSeek Coder V2 16B benchmark scores

Benchmark verified

Coding

SWE-bench Verified
HumanEval+81.1%
Aider Polyglot
LiveCodeBench24.3%

Hardware-Kompatibilität

Eignungsschätzungen für alle Hardware

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Computing compatibility...

Speicheraufschlüsselung

Reference: RTX 2060 6GB

Weights9.8 GB
KV Cache3.3 GB
Runtime1.2 GB
Headroom0.6 GB

Häufig gestellte Fragen

FAQ — DeepSeek Coder V2 16B

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