Text / Qwen
Qwen3 8B
An open-weight language model with switchable thinking and non-thinking modes.
Not yet tested
LOCALCLOUDOPEN WEIGHTS
This is a source-based starting point. We haven’t independently tested this model yet. Source-based estimates are separate from our test results. Measured speed and our verdict will appear after a reproducible test.
At a glance
- Parameters
- 8.2B
- Architecture
- Dense transformer
- Context length
- 32,768 native
- License
- Apache 2.0
- Recommended VRAM
- Not yet tested
- Minimum tested VRAM
- Not yet tested
- Disk space
- Not yet tested
- Software
- Ollama, llama.cpp
HARDWARE ESTIMATE
What will it need?
Our test notes
Not yet tested. We’ll publish the hardware, quantization, context, speed, peak memory, and load time together. A parameter count alone is not a hardware requirement.
Our verdict
Not yet tested. Check the publisher’s documentation for capabilities and limitations; we’ll add an independent verdict after testing.
Explore its uses
REASONINGCHATMULTILINGUAL
Get it running
Your first local Qwen setup
Install Ollama, download Qwen3, and start a conversation on your own machine.
View workflowKeep exploring
Text
DeepSeekDeepSeek V4.1 Flash
A multimodal reasoning model with a compressed key-value cache, published as open weights.
MODEL SIZENot specified
Text
QwenQwen3.8-Flash-Next
An experimental open-weight multimodal model with sparse attention and 262K native context.
MODEL SIZE125B language · 6B active
Text
DeepSeekDeepSeek R1 · 14B
A distilled reasoning model built on Qwen2.5, for exploring reasoning on your own infrastructure.
MODEL SIZE14B