Qwen just released the Qwen3.5 Small Model Series — 0.8B, 2B, 4B and 9B. Native multimodal with improved architecture and scaled RL. 0.8B and 2B are tiny and fast for edge devices, 4B makes a strong lightweight agent base, and 9B is already closing the gap with much larger models. Base versions released too.
The Qwen team just dropped the Qwen3.5 Small Model Series: 0.8B, 2B, 4B, and 9B, along with their Base versions.
This release fills the missing piece for on-device deployment and completes the full Qwen3.5 matrix from 0.8B all the way to 397B. Now you have clear choices:
Really cool to see Qwen3 pushing open-source AI forward; the hybrid reasoning + fast response approach is super interesting. Curious to know, what kinds of real-world applications or agents are you most excited to see people build with it?
The benchmarks on the 9B model are seriously wild - matching models 13x its size is no small feat, and having the full range from 0.8B to 9B gives developers real flexibility for edge deployment. Curious though: how does the multimodal performance hold up on the smaller 0.8B and 2B variants compared to the 9B?
may i ask which models the best for unity game engine problem solving?
Native multimodal at 0.8B is genuinely impressive - most teams trade off size for capability, but 262K context windows + text/image/video in under 1B parameters changes the edge deployment math.
The 9B beating GPT-OSS-20B on GPQA Diamond is interesting. Curious about structured output reliability at 0.8B though - small models tend to drop JSON schema adherence under complex instructions. Is there a differentiated training approach for structured data tasks?
MTP for faster inference on constrained hardware is a smart addition. Real-world throughput numbers on consumer GPU vs Apple Silicon would help developers size their deployment targets.
The 9B punching above its weight class is the real story here. Running capable models locally without needing a data center changes what's possible for privacy-conscious apps and edge deployments. Been waiting for small open-source models to close this gap.
The 9B matching models that size is wild — smaller models getting this good makes edge + local AI way more practical than most people realize.
“0.8B-9B native multimodal w/ more intelligence, less compute”
Qwen3.5 Small launched on Product Hunt on March 3rd, 2026 and earned 384 upvotes and 14 comments, earning #2 Product of the Day. Qwen just released the Qwen3.5 Small Model Series — 0.8B, 2B, 4B and 9B. Native multimodal with improved architecture and scaled RL. 0.8B and 2B are tiny and fast for edge devices, 4B makes a strong lightweight agent base, and 9B is already closing the gap with much larger models. Base versions released too.
Qwen3.5 Small was featured in Open Source (68.3k followers), Privacy (11k followers) and Artificial Intelligence (466.2k followers) on Product Hunt. Together, these topics include over 103.6k products, making this a competitive space to launch in.
Who hunted Qwen3.5 Small?
Qwen3.5 Small was hunted by Zac Zuo. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Zac Zuo
Hi everyone!
The Qwen team just dropped the Qwen3.5 Small Model Series: 0.8B, 2B, 4B, and 9B, along with their Base versions.
This release fills the missing piece for on-device deployment and completes the full Qwen3.5 matrix from 0.8B all the way to 397B. Now you have clear choices:
0.8B/2B for embedded/IoT/Mobile
4B for lightweight multimodal agents
9B for edge servers
Plus the bigger MoE models for heavier workloads.
The 9B is the real shocker: matching or beating GPT-OSS-120B on several key benchmarks while being 13x smaller.
Even Elon chimed in:
Edge AI is heating up fast. This opens up exciting new opportunities for AI hardware and local innovation.
Play with these models on @Ollama!