What are the hardware requirements for XwinCoder 34B?

XwinCoder 34B requires approximately 67.5 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed XwinCoder 34B and how large is it?

XwinCoder 34B is developed by Xwin-LM, 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 XwinCoder 34B perform on standard benchmarks?

XwinCoder 34B has the following published scores: MMLU 49.53. Compare against reference models on this page or on the LLM Explorer leaderboards.

XwinCoder 34B by Xwin-LM — VRAM 67.5GB, 16K context

Name: XwinCoder 34B
Author: Xwin-LM

XwinCoder 34B is an open-source language model by Xwin-LM. Features: 34b LLM, VRAM: 67.5GB, Context: 16K, License: llama2, Code Generating, LLM Explorer Score: 0.12, Arc: 51, HellaSwag: 74, MMLU: 49.5, GSM8K: 39.4.

Codegen Endpoints compatible Llama Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/Xwin-LM/XwinCoder-34B

XwinCoder 34B Benchmarks

LLME Score: 0.12491

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

XwinCoder 34B Parameters and Internals

Model Type

code generation

Additional Notes

XwinCoder models are instruction finetuned code generation models based on CodeLLaMA.

LLM Name	XwinCoder 34B
Repository 🤗	https://huggingface.co/Xwin-LM/XwinCoder-34B
Model Size	34b
Required VRAM	67.5 GB
Updated	2026-07-16
Maintainer	Xwin-LM
Model Type	llama
Model Files	9.8 GB: 1-of-7 9.7 GB: 2-of-7 9.7 GB: 3-of-7 9.7 GB: 4-of-7 9.7 GB: 5-of-7 9.7 GB: 6-of-7 9.2 GB: 7-of-7
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	16384
Model Max Length	16384
Transformers Version	4.34.1
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	bfloat16

Quantized Models of the XwinCoder 34B

Model	Likes	Downloads	VRAM
XwinCoder 34B GGUF	10	121	14 GB
XwinCoder 34B GPTQ	2	7	17 GB
XwinCoder 34B AWQ	1	4	18 GB

Best Alternatives to XwinCoder 34B

Best Alternatives	Context / RAM	Downloads	Likes
...gpt 32K Codellama 34B Instruct	32K / 67.5 GB	56	2
CodeLlama 34B Instruct Hf	16K / 67.5 GB	57493	304
CodeLlama 34B Instruct Hf	16K / 1.4 GB	5	3
ReflectionCoder CL 34B	16K / 67.6 GB	8067	0
Speechless Codellama 34B V2.0	16K / 67.5 GB	96	17
Phind CodeLlama 34B V2	16K / 67.5 GB	618	834
CodeLlama 34B Hf	16K / 67.5 GB	27673	178
Phind CodeLlama 34B V1	16K / 67.5 GB	165	320
Phind CodeLlama 34B Python V1	16K / 67.5 GB	180	252
CodeLlama 34B Python Hf	16K / 67.5 GB	459	99

Note: green Score (e.g. "73.2") means that the model is better than Xwin-LM/XwinCoder-34B.

Rank the XwinCoder 34B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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

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Release v20260328a

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XwinCoder 34B by Xwin-LM