# Qwen3.5-2B by Qwen: Open-Weight Model
Source: https://savrn.com/models/qwen3-5-2b
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

---

## Runs On

What it takes to serve Qwen3.5-2B (2.3B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
| --- | --- | --- | --- | --- | --- |
| 16-bit | 4.5 GB | 5.5 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |
| 8-bit | 2.3 GB | 2.7 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |
| 4-bit | 1.1 GB | 1.4 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the [SAVRN Index](https://savrn.com/ai-index/pricing/gpus), read Oct 23, 2026.

[Qwen3.5-2B on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/qwen3-5-2b/gpus)

## SAVRN's Notes on Qwen3.5-2B

2.3B parameters, image and text in, text out, over a 262,144-token context: 5.5 GB at 16-bit, 2.7 GB at 8-bit and 1.4 GB at 4-bit on the one 192 GB MI300X at $1.85 an hour that anchors our small-model pricing — the weights take a sliver and the long context fills the rest. This is the entry point of Qwen's natively multimodal 3.5 line, first published 2026-02-28 at 4.8M downloads a month.

Apache 2.0 covers commercial use, modification and redistribution. Reported scores — GPQA Diamond 44.9495, MMLU-Pro 55.3 — set honest expectations: this is the edge and appliance tier, and the derived list includes Rockchip RK182X LLM and VLM ports, which tells you where the community is taking it. For a bigger multimodal step, the 4B sibling doubles capacity for roughly twice the memory.

SAVRN Research

## Model Card

By Qwen, published under apache-2.0, revision 15852e8c1636.

[!Note] This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format.

These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc.

In light of its parameter scale, the intended use cases are prototyping, task-specific fine-tuning, and other research or development purposes.

Over recent months, we have intensified our focus on developing foundation models that deliver exceptional utility and performance. Qwen3.5 represents a significant leap forward, integrating breakthroughs in multimodal learning, architectural efficiency, reinforcement learning scale, and global accessibility to empower developers and enterprises with unprecedented capability and efficiency.

### Qwen3.5 Highlights

Qwen3.5 features the following enhancement:

[Read the full model card (2,815 words)](https://savrn.com/models/qwen3-5-2b/card)

## Configuration

Architecture

Qwen3_5ForConditionalGeneration

Context length (tokens)

262,144

Layers

24

Hidden size

2,048

Feed-forward size

6,144

Attention heads

8

Key/value heads

2

Head dimension

256

Vocabulary size

248,320

Model type

qwen3_5

## Identity and Version

Repository

Qwen/Qwen3.5-2B

Publisher

Qwen

Task

Image and text to text

Modality

Image and text

Library

transformers

Parameters

2.3B parameters

Languages

Not stated by the source

Revision

15852e8c16360a2fea060d615a32b45270f8a8fc

First published

2026-02-28

Last updated

2026-03-02

## Files and Weights

13 files, 4.6 GB in total. The weights are 1 file totalling 4.5 GB in safetensors.

Weights1 file · 4.5 GB

Configuration4 files · 68.1 KB

Tokenizer4 files · 22.9 MB

Documentation2 files · 74.4 KB

Other1 file · 7.8 KB

Repository1 file · 1.6 KB

Every file

| File | Type | Size | SHA-256 |
| --- | --- | --- | --- |
| model.safetensors-00001-of-00001.safetensors | Weights | 4.5 GB | aa33250c4fc6 |
| config.json | Configuration | 2.9 KB | — |
| model.safetensors.index.json | Configuration | 64.5 KB | — |
| preprocessor_config.json | Configuration | 390 B | — |
| video_preprocessor_config.json | Configuration | 385 B | — |
| LICENSE | Documentation | 11.5 KB | — |
| README.md | Documentation | 62.8 KB | — |
| chat_template.jinja | Other | 7.8 KB | — |
| .gitattributes | Repository | 1.6 KB | — |
| merges.txt | Tokenizer | 3.4 MB | — |
| tokenizer.json | Tokenizer | 12.8 MB | 5f9e4d4901a9 |
| tokenizer_config.json | Tokenizer | 16.7 KB | — |
| vocab.json | Tokenizer | 6.7 MB | — |

## License and Download

License

apache-2.0

Access

Open weights, no gate

Download size

4.5 GB

[Download from Qwen](https://modelscope.cn/models/Qwen/Qwen3.5-2B)

Released by Qwen through ModelScope. [Read the license](https://www.apache.org/licenses/LICENSE-2.0).

## Built From

- Derived from Qwen/Qwen3.5-2B-Base

## Evaluations

Each result is shown as reported, with the conditions its reporter stated. None is a SAVRN measurement. A comparison lines two results up only when their configuration, unit and setup are all stated and identical.

| Benchmark | Conditions | Result | Reported by | Revision | Date |
| --- | --- | --- | --- | --- | --- |
| Idavidrein/gpqa | Task diamondMetric diamondSetup GPQA DiamondComparison conditions not established | 44.9495 | [EvalEval](https://huggingface.co/datasets/evaleval/EEE_datastore/blob/192329fb7d6b15b7b0936a1a58ae862aa7e8ba24/flat/objects/9a/b3/9ab3daf6-462a-47bc-8061-1e2222bffa3d.json) Reported by a third party | Evaluated revision not stated | 2026-04-20 |
| LiquidAI/ifstruct-v1.0 | Task ifstruct_v1Metric ifstruct_v1Comparison conditions not established | 33.15 | Liquid AI — IFStruct v1.0 blog (Qwen3.5-2B) Reported by a third party | Evaluated revision not stated | 2026-06-30 |
| MMMU/MMMU_Pro | Task mmmu_pro_visionMetric mmmu_pro_visionSetup ThinkingComparison conditions not established | 50.3 | [Model Card](https://huggingface.co/Qwen/Qwen3.5-2B) Reported by a third party | Evaluated revision not stated | 2026-04-28 |
| TIGER-Lab/MMLU-Pro | Task mmlu_proMetric mmlu_proComparison conditions not established | 55.3 | [Model Card](https://huggingface.co/Qwen/Qwen3.5-2B) Reported by a third party | Evaluated revision not stated | 2026-03-02 |
| likaixin/ScreenSpot-Pro | Task overallMetric overallComparison conditions not established | 54.5 | [Model Card](https://huggingface.co/Qwen/Qwen3.5-2B) Reported by a third party | Evaluated revision not stated | 2026-03-18 |
| llamaindex/ExtractBench | Task longMetric longSetup Pipeline name: qwen3_5_2b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 25.93 | [ExtractBench](https://huggingface.co/datasets/llamaindex/ExtractBench) Reported by a third party | Evaluated revision not stated | 2026-08-24 |
| llamaindex/ExtractBench | Task meanMetric meanSetup Pipeline name: qwen3_5_2b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 63.4 | [ExtractBench](https://huggingface.co/datasets/llamaindex/ExtractBench) Reported by a third party | Evaluated revision not stated | 2026-08-24 |
| llamaindex/ExtractBench | Task mediumMetric mediumSetup Pipeline name: qwen3_5_2b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 50.93 | [ExtractBench](https://huggingface.co/datasets/llamaindex/ExtractBench) Reported by a third party | Evaluated revision not stated | 2026-08-24 |
| llamaindex/ExtractBench | Task shortMetric shortSetup Pipeline name: qwen3_5_2b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 71.22 | [ExtractBench](https://huggingface.co/datasets/llamaindex/ExtractBench) Reported by a third party | Evaluated revision not stated | 2026-08-24 |
| llamaindex/ParseBench | Task chartMetric chartSetup Pipeline name: qwen3_5_2b_vllm_layoutComparison conditions not established | 0.1 | [ParseBench](https://huggingface.co/datasets/llamaindex/ParseBench) Reported by a third party | Evaluated revision not stated | 2026-04-22 |
| llamaindex/ParseBench | Task layoutMetric layoutSetup Pipeline name: qwen3_5_2b_vllm_layoutComparison conditions not established | 18.3 | [ParseBench](https://huggingface.co/datasets/llamaindex/ParseBench) Reported by a third party | Evaluated revision not stated | 2026-04-22 |
| llamaindex/ParseBench | Task meanMetric meanSetup Pipeline name: qwen3_5_2b_vllm_layoutComparison conditions not established | 27.3 | [ParseBench](https://huggingface.co/datasets/llamaindex/ParseBench) Reported by a third party | Evaluated revision not stated | 2026-04-22 |
| llamaindex/ParseBench | Task tableMetric tableSetup Pipeline name: qwen3_5_2b_vllm_layoutComparison conditions not established | 0 | [ParseBench](https://huggingface.co/datasets/llamaindex/ParseBench) Reported by a third party | Evaluated revision not stated | 2026-04-22 |
| llamaindex/ParseBench | Task text_contentMetric text_contentSetup Pipeline name: qwen3_5_2b_vllm_layoutComparison conditions not established | 87.2 | [ParseBench](https://huggingface.co/datasets/llamaindex/ParseBench) Reported by a third party | Evaluated revision not stated | 2026-04-22 |
| llamaindex/ParseBench | Task text_formattingMetric text_formattingSetup Pipeline name: qwen3_5_2b_vllm_layoutComparison conditions not established | 31.1 | [ParseBench](https://huggingface.co/datasets/llamaindex/ParseBench) Reported by a third party | Evaluated revision not stated | 2026-04-22 |

## Memory Requirements

| Precision | Weights in memory |
| --- | --- |
| As published | 4.5 GB |
| 16-bit | 4.5 GB |
| 8-bit | 2.3 GB |
| 4-bit | 1.1 GB |

Weights only, from the published parameter count; the key-value cache and runtime add to this.

## Built on This Model

- Quantized from[Qwen3.5-2B-RKLLM](https://savrn.com/models/qwen3-5-2b-rkllm)
- Derived from[Qwen3.5-2B-RKLLM](https://savrn.com/models/qwen3-5-2b-rkllm)
- Derived from[dQwen3.5-2B-Base](https://savrn.com/models/dqwen3-5-2b-base)
- Derived from[Valen-2B](https://savrn.com/models/valen-2b)
- Derived from[Qwen3.5-2B-DSpark](https://savrn.com/models/qwen3-5-2b-dspark)
- Derived from[Decision-1.0-Sol-2B](https://savrn.com/models/decision-1-0-sol-2b)
- Derived from[GameScaling-2B-S3](https://savrn.com/models/gamescaling-2b-s3)
- Derived from[GameScaling-2B-S1](https://savrn.com/models/gamescaling-2b-s1)
- Derived from[KeyVoice-Refiner-2B-v0.1](https://savrn.com/models/keyvoice-refiner-2b-v0-1)
- Quantized from[RK182X-LLM-Qwen3.5-2B](https://savrn.com/models/rk182x-llm-qwen3-5-2b)
- Derived from[RK182X-LLM-Qwen3.5-2B](https://savrn.com/models/rk182x-llm-qwen3-5-2b)
- Derived from[Qwen3.5-2B-auto-optimized](https://savrn.com/models/qwen3-5-2b-auto-optimized)
- Adapter of[dual-loop-qwen3.5-2b](https://savrn.com/models/dual-loop-qwen3-5-2b)
- Derived from[dual-loop-qwen3.5-2b](https://savrn.com/models/dual-loop-qwen3-5-2b)
- Quantized from[wag-2b](https://savrn.com/models/wag-2b)
- Derived from[wag-2b](https://savrn.com/models/wag-2b)
- Adapter of[weather-rescue-brazil-reader](https://savrn.com/models/weather-rescue-brazil-reader)
- Derived from[weather-rescue-brazil-reader](https://savrn.com/models/weather-rescue-brazil-reader)
- Adapter of[vnpen-writer-2b-v0.1-preview](https://savrn.com/models/vnpen-writer-2b-v0-1-preview)
- Derived from[vnpen-writer-2b-v0.1-preview](https://savrn.com/models/vnpen-writer-2b-v0-1-preview)
- Quantized from[RK182X-VLM-Qwen3.5-2B](https://savrn.com/models/rk182x-vlm-qwen3-5-2b)
- Derived from[RK182X-VLM-Qwen3.5-2B](https://savrn.com/models/rk182x-vlm-qwen3-5-2b)
- Derived from[DN-MOPD-Qwen3.5-2B-baseline-label-160updates](https://savrn.com/models/dn-mopd-qwen3-5-2b-baseline-label-160updates)
- Derived from[DN-MOPD-Qwen3.5-2B-160updates](https://savrn.com/models/dn-mopd-qwen3-5-2b-160updates)
- Derived from[ThinkLess-2B](https://savrn.com/models/thinkless-2b)
- Derived from[Qwen3.5-2B-MLP](https://savrn.com/models/qwen3-5-2b-mlp)
- Derived from[MaLoW-Qwen3.5-2B-MLP](https://savrn.com/models/malow-qwen3-5-2b-mlp)
- Derived from[MaLoW-Qwen3.5-2B](https://savrn.com/models/malow-qwen3-5-2b)
- Derived from[Qwen3.5-2B-tool-router-v2-q4f16_1-MLC](https://savrn.com/models/qwen3-5-2b-tool-router-v2-q4f16-1-mlc)
- Derived from[Qwen3.5-2B-tool-router-v2-q4f32_1-MLC](https://savrn.com/models/qwen3-5-2b-tool-router-v2-q4f32-1-mlc)
- Adapter of[udm_qwen3.5-2b_v2](https://savrn.com/models/udm-qwen3-5-2b-v2)
- Derived from[udm_qwen3.5-2b_v2](https://savrn.com/models/udm-qwen3-5-2b-v2)
- Derived from[uratori-ja-2b](https://savrn.com/models/uratori-ja-2b)
- Derived from[OpenSLA](https://savrn.com/models/opensla)
- Quantized from[Qwen3.5-2B-RCOL](https://savrn.com/models/qwen3-5-2b-rcol)
- Derived from[Qwen3.5-2B-RCOL](https://savrn.com/models/qwen3-5-2b-rcol)
- Quantized from[Qwen3.5-2B-JNS](https://savrn.com/models/qwen3-5-2b-jns)
- Derived from[Qwen3.5-2B-JNS](https://savrn.com/models/qwen3-5-2b-jns)
- Derived from[d3-nano](https://savrn.com/models/d3-nano)
- Derived from[Qwen3.5-2B-dragon_dose-STEER0.0797-ft4.42](https://savrn.com/models/qwen3-5-2b-dragon-dose-steer0-0797-ft4-42)

## Compare Qwen3.5-2B

- [Qwen3.5-2B vs Rax-4.5](https://savrn.com/models/compare/qwen3-5-2b-vs-rax-4-5)
- [Qari-OCR-v0.3-VL-2B-Instruct vs Qwen3.5-2B](https://savrn.com/models/compare/qari-ocr-v0-3-vl-2b-instruct-vs-qwen3-5-2b)
- [Qwen2-VL-2B-Instruct vs Qwen3.5-2B](https://savrn.com/models/compare/qwen2-vl-2b-instruct-vs-qwen3-5-2b)

## Questions About Qwen3.5-2B

### How much GPU memory does Qwen3.5-2B need?

About 5.5 GB at 16-bit and 1.4 GB at 4-bit: the weights (2.3B parameters) plus a working margin. A long context needs more.

### What is the cheapest GPU to run Qwen3.5-2B on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

### Can I use Qwen3.5-2B commercially?

Yes. Qwen3.5-2B is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

### What is Qwen3.5-2B's context length?

262,144 tokens, from the maximum position embeddings in its published configuration.

## Similar Models

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Open weights apache-2.0 2.2B parameters 262,144 tokens transformers

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### [Qwen3.5-2B-Base-heretic](https://savrn.com/models/qwen3-5-2b-base-heretic)

[Roumiany](https://savrn.com/model-publishers/aminroumiany)

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### [Qwen3.5-2B-Vi-SFT-VLM-v2.1](https://savrn.com/models/qwen3-5-2b-vi-sft-vlm-v2-1)

[Pham Phuc](https://savrn.com/model-publishers/phuc-hugigface)

This is the model card of a transformers model that has been pushed on the Hub. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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[XinLi](https://savrn.com/model-publishers/xinli1997)

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Open weights apache-2.0 2.2B parameters 262,144 tokens transformers

[View model](https://savrn.com/models/dn-mopd-qwen3-5-2b-baseline-label-160updates)

## Qwen

[All models and datasets](https://savrn.com/model-publishers/qwen)

## Versions

- [15852e8c1636](https://savrn.com/models/qwen3-5-2b/versions/15852e8c1636) · current 2026-10-23

## Explore More

- [All image and text to text models](https://savrn.com/models/tasks/image-and-text-to-text)
- [All models under apache-2.0](https://savrn.com/models/licenses/apache-2-0)
- [Model comparisons](https://savrn.com/models/comparisons)
- [The model directory](https://savrn.com/models)
- [Open model prices by host](https://savrn.com/ai-index/pricing/open-models)

## Source

- Repository metadata, read 2026-10-19.
- [Qwen website](https://qwen.ai/)
- [Hugging Face record](https://huggingface.co/Qwen/Qwen3.5-2B)
- [How the hub is built](https://savrn.com/model-hub/methodology)