Particle-1 vs Qwen3 VL 30B A3B Thinking
Particle-1 leads the LLM Stats Score 31.9 to 17.7. Qwen3 VL 30B A3B Thinking is 1.1x cheaper per token.
Particle AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Particle-1 leads the overall LLM Stats Score 31.9 to 17.7, ranking #133 overall.
The models split the 2 individual benchmarks reported for both models evenly.
On price, Qwen3 VL 30B A3B Thinking is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Particle-1 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Particle-1
- overall performance matters — it scores 31.9 and ranks #133 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
Choose Qwen3 VL 30B A3B Thinking
- cost matters — it's about 1.1x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
3 reported for Particle-1 · 50 for Qwen3 VL 30B A3B Thinking
Particle-1 outperforms in 1 benchmarks (GPQA), while Qwen3 VL 30B A3B Thinking is better at 1 benchmark (MMLU).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Particle-1 ($0.25/1M tokens) is 1.3x more expensive than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).
For output processing, Particle-1 ($1.00/1M tokens) is 1.0x more expensive than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).
In conclusion, Particle-1 is more expensive than Qwen3 VL 30B A3B Thinking.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Particle-1 accepts 1,048,576 input tokens compared to Qwen3 VL 30B A3B Thinking's 131,072 tokens. Particle-1 can generate longer responses up to 131,072 tokens, while Qwen3 VL 30B A3B Thinking is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Both Particle-1 and Qwen3 VL 30B A3B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Particle-1
Qwen3 VL 30B A3B Thinking
License
Usage and distribution terms
Particle-1 is licensed under a proprietary license, while Qwen3 VL 30B A3B Thinking uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Particle-1 was released on 2026-10-28, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.
Particle-1 is 13 months newer than Qwen3 VL 30B A3B Thinking.
Oct 28, 2026
-1 days ago
1.1yr newerSep 22, 2025
1.1 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Particle-1 is available from Particle AI. Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra.
Particle-1
Qwen3 VL 30B A3B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Particle-1 and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Particle-1 vs Qwen3 VL 30B A3B Thinking.