Shin L4 yana da saurin da ya isa don tattaunawar LLM?

Ga samfuran 7B–14B, eh. Saurin ƙwaƙwalwarsa na 221 GB/s memory bandwidth yana iyakance tokens a kowace daƙiƙa idan aka kwatanta da RTX 4090 ko A100, don haka ya fi dacewa da ƙarancin masu amfani a lokaci ɗaya da ayyukan rukuni fiye da ɗaukar manyan cunkoson jama'a.

L4 da RTX 4090: wanne ya kamata in yi hayarsa?

An jera RTX 4090 da 24 GB, 81.4 TFLOPS da 879 GB/s, don haka yana da sauri sosai. Shi kuma L4 zaɓi ne na datacenter mai amfani da ƙarancin wuta (72 W) tare da 22 GB, wanda yake da kyau idan buƙatar aiki da gudu matsakaiciya ce.

Shin L4 zai iya gudanar da Stable Diffusion da Flux?

Eh. SD 1.5 da SDXL suna aiki da kyau, kuma Flux yana aiki a yanayin FP8 ko quantized GGUF. Yi tsammanin fitar da hotuna a hankali fiye da manyan katunan Ada, tunda FP32 kusan 24.2 TFLOPS ne.

Yaya Cloudj ke karɓar kuɗin sabar L4?

A kowace sa'a lokacin da take aiki daga ma'aunin asusunka, ko kuma a tsarin kowane wata ko fiye da haka tare da kowane rangwame da aka nuna kafin biya. Sabar da aka tsayar wadda ake biya a duk sa'a ana karɓar kuɗin faifan ajiyarta kawai.

GPU Cloud · NVIDIA · Ada Lovelace

Yi Hayar GPU ta NVIDIA L4 Mai 22 GB VRAM

Yi hayar sabar L4 cloud GPU a duk sa'a a Cloudj: 22 GB VRAM, tsarin gini na Ada Lovelace da kusan 24.2 TFLOPS FP32 a kan ƙarfin wuta 72 W kacal. Ya dace da masu haɓaka manhaja da ke gudanar da ingantaccen inference, transcription, embeddings da tsarin bidiyo waɗanda ke son ƙarin ƙwaƙwalwar ajiya fiye da katin 8–16 GB ba tare da biyan kuɗin babban katin zamani ba. Fara daga samfurin PyTorch, vLLM ko Ollama sannan ka haɗa ta SSH.

Yi hayar L4 Duk GPUs

Bayanan fasaha na L4

VRAM a kowace GPU

22 GB

Ginin fasaha

NVIDIA Ada Lovelace

Ikon lissafi (Compute capability)

8.9

Lissafin FP32

≈ 24.2 TFLOPS

Gudun ƙwaƙwalwa (Bandwidth)

≈ 221 GB/s

Ƙayyadaddun wutar lantarki

72 W

Ƙimomin da mai samar da kayan aiki ya bayar don na'urorin da aka jera a yanzu; ainihin aikin ya bambanta dangane da na'ura.

Tsare-tsare da farashin L4 na yanzu

Kayan da ke akwai da farashin kai tsaye, ana sabunta su akai-akai. Ana tabbatar da farashin ƙarshe kafin ka yi oda.

Yi haya yanzu

Abubuwan da za ka iya gudanarwa a kan cloud GPU na L4

LLMs na 7B–8B a 16-bit

22 GB na ɗaukar samfurin 8B a 16-bit ko samfurin 13B–14B da aka yi wa quantized don chatbots, agents da APIs na ciki.

Mayar da murya zuwa rubutu da embeddings

Gudanar da transcription irin na Whisper, rerankers da samfuran embedding dare da rana a kan katin da ke cin ƙarancin wuta.

Ƙirƙirar hotuna da SDXL

ComfyUI tare da SDXL da Flux a yanayin FP8 ko GGUF na shiga cikin sauƙi a 22 GB.

Tashoshin inference da ke aiki a kowane lokaci

Ƙarancin ƙarfin wuta na 72 W ya sa L4 ya zama katin da ya dace da ƙananan ayyuka da ke buƙatar ci gaba da aiki ba tsayawa maimakon aiki mai ɗaukar lokaci kaɗan.

Shin L4 ita ce GPU da ta dace da aikinku?

Zaɓi L4 idan kana buƙatar 22 GB na VRAM da Ada Lovelace compute capability 8.9 don inference ko ayyukan horar da samfura masu matsakaicin girma. Sauya zuwa babban datacenter GPU idan samfuranka sun haura 22 GB ko kuma suna buƙatar memory bandwidth sama da kusan 221 GB/s, ko kuma ka zaɓi ƙaramin kati don ayyukan haɓaka manhaja na asali waɗanda ke buƙatar ƙarancin ƙwaƙwalwa.

L4 idan aka kwatanta da sauran cloud GPU

GPU	VRAM a kowace GPU	Lissafin FP32	Ƙayyadaddun wutar lantarki
NVIDIA L4	22 GB	≈ 24.2 TFLOPS	72 W
NVIDIA Tesla P40	24 GB	≈ 9.4 TFLOPS	250 W	Cikakken bayani →
NVIDIA Tesla V100	16 GB	≈ 12.5 TFLOPS	300 W	Cikakken bayani →
NVIDIA A100 PCIE	40 GB	≈ 15.6 TFLOPS	250 W	Cikakken bayani →
NVIDIA A100 SXM4	40 GB	≈ 15.6 TFLOPS	400 W	Cikakken bayani →

Cloud GPU na L4: tambayoyin da aka fi yi

Yi hayar cloud GPU na L4 a kowace sa'a

Zaɓi samfuri, zaɓi tsari na kai tsaye, sannan ka haɗa ta SSH ko terminal na browser. Caji na tsayawa da zarar ka goge GPU ɗin.

Yi hayar L4 Duk GPUs