InternLM
InternLM 20B
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1.1KDownloads94LikesJul 2024Veröffentlicht8K TokenKontextInternLMLizenz22 EinstiegQualität
InternLM 20B (20B parameters) requires approximately 34.2 GB of VRAM with Q5_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 40 GB of VRAM.
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— kopieren & einfügen, um lokal auszuführenCopy-paste commands to run InternLM 20B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "internlm/internlm2_5-20b-chat" \
--hf-file "internlm2_5-20b-chat-Q5_K_M.gguf" \
-c 4096 -ngl 99Quick specs
Parameters20B
Architecturedense
Context8K tokens
Modalitytext
Min RAM7.8 GB
Rec. RAM14.4 GB (Q5_K_M)
LicenseInternLM
FamilyInternLM
✓ Code✓ Chat
About this model
- •Outstanding reasoning capability: State-of-the-art performance on Math reasoning, surpassing models like Llama3 and Gemma2-27B
- •Stronger tool use: InternLM2.5 supports gathering information from more than 100 web pages, corresponding implementation has be released in...
Verwandte Modelle
Schnellauswahl
Beste Hardware
Top-Empfehlungen für InternLM 20B
Dieses Modell ausführen
Quantisierungsoptionen
VRAM-Schätzungen nach Quantisierungsstufe
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 7.8 GB | Low | — |
Q3_K_S | 3 | 9.8 GB | Low | — |
NVFP4 | 4 | 11.2 GB | Medium | — |
Q4_K_M | 4 | 12.2 GB | Medium | — |
Q5_K_M | 5 | 14.4 GB | High | — |
Q6_K | 6 | 16.4 GB | High | — |
Q8_0 | 8 | 21.4 GB | Very High | — |
F16 | 16 | 41.0 GB | Maximum | — |
Quality benchmarks
InternLM 20B benchmark scores
Reasoning
MMLU-Pro33.3%
GPQA Diamond9.5%
MATH-50040.8%
ARC Challenge—
General
Chatbot Arena—
IFEval70.1%
Source: community · 2025-01-01
Hardware-Kompatibilität
Eignungsschätzungen für alle Hardware
Computing compatibility...
Speicheraufschlüsselung
Reference: RTX 2060 6GB
Weights14.4 GB
KV Cache18.3 GB
Runtime0.9 GB
Headroom0.6 GB
Häufig gestellte Fragen
FAQ — InternLM 20B
Siehe auch