What are the hardware requirements for Yi 34B 200K AEZAKMI RAW 1701?

Yi 34B 200K AEZAKMI RAW 1701 requires approximately 69.2 GB of VRAM and supports a context window of 195K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Yi 34B 200K AEZAKMI RAW 1701 and how large is it?

Yi 34B 200K AEZAKMI RAW 1701 is developed by adamo1139, a model with 34b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Yi 34B 200K AEZAKMI RAW 1701 perform on standard benchmarks?

Yi 34B 200K AEZAKMI RAW 1701 has the following published scores: MMLU 75.44. Compare against reference models on this page or on the LLM Explorer leaderboards.

Yi 34B 200K AEZAKMI RAW 1701 by adamo1139 — VRAM 69.2GB, 195K context

Name: Yi 34B 200K AEZAKMI RAW 1701
Author: adamo1139

Yi 34B 200K AEZAKMI RAW 1701 is an open-source language model by adamo1139. Features: 34b LLM, VRAM: 69.2GB, Context: 195K, License: apache-2.0, LLM Explorer Score: 0.12, Arc: 66.8, HellaSwag: 85.8, MMLU: 75.4, GSM8K: 60.

Dpo Endpoints compatible Fine tune Finetuned Llama Model-index Region:us Safetensors Sft Sharded Tensorflow Yi

Model Card on HF 🤗: https://huggingface.co/adamo1139/Yi-34B-200K-AEZAKMI-RAW-1701

Yi 34B 200K AEZAKMI RAW 1701 Parameters and Internals

Model Type

text-generation

Additional Notes

This model is experimental and might be buggy. The strength of DPO and SFT is not perfected yet.

Training Details

Methodology:

Yi-34B-200K trained via DPO on RAWrr_v1 at ctx 200 (lora_r 4, lora_alpha 8) and then via SFT at ctx 1400 (lora_r 16, lora_alpha 32) on AEZAKMI_v2.

LLM Name	Yi 34B 200K AEZAKMI RAW 1701
Repository 🤗	https://huggingface.co/adamo1139/Yi-34B-200K-AEZAKMI-RAW-1701
Model Size	34b
Required VRAM	69.2 GB
Updated	2026-06-05
Maintainer	adamo1139
Model Type	llama
Model Files	4.8 GB: 1-of-15 4.8 GB: 2-of-15 5.0 GB: 3-of-15 4.8 GB: 4-of-15 4.8 GB: 5-of-15 5.0 GB: 6-of-15 4.8 GB: 7-of-15 4.8 GB: 8-of-15 5.0 GB: 9-of-15 4.8 GB: 10-of-15 4.8 GB: 11-of-15 5.0 GB: 12-of-15 4.8 GB: 13-of-15 4.8 GB: 14-of-15 1.2 GB: 15-of-15
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	200000
Model Max Length	200000
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	64000
Torch Data Type	float16

Rank the Yi 34B 200K AEZAKMI RAW 1701 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Quantized Models of the Yi 34B 200K AEZAKMI RAW 1701

Model	Likes	Downloads	VRAM
...34B 200K Aezakmi Raw 1902 EXL2	1	3	20 GB

Best Alternatives to Yi 34B 200K AEZAKMI RAW 1701

Best Alternatives	Context / RAM	Downloads	Likes
Bagel Hermes 34B Slerp	195K / 68.9 GB	8375	1
34B Beta	195K / 69.2 GB	8670	67
Smaug 34B V0.1	195K / 69.2 GB	8082	64
Casual Magnum 34B	195K / 68.8 GB	4	1
Yi 34B 200K	195K / 68.9 GB	9133	320
Bagel 34B V0.2	195K / 68.7 GB	259	41
Yi 34B 200K AEZAKMI V2	195K / 69.2 GB	57	12
Faro Yi 34B	195K / 69.2 GB	8208	6
Bagel DPO 34B V0.5	195K / 68.7 GB	8040	17
Smaug 34B V0.1 ExPO	195K / 69.2 GB	7812	0

Note: green Score (e.g. "73.2") means that the model is better than adamo1139/Yi-34B-200K-AEZAKMI-RAW-1701.