Particle-1 vs Qwen3 VL 8B Thinking
Particle-1 leads the LLM Stats Score 31.9 to 15.7. Particle-1 is 1.5x 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 15.7, ranking #133 overall.
In the 2 individual benchmarks reported for both models, Particle-1 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Particle-1 is roughly 1.5x 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 value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 1.5x cheaper per token
- 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 8B Thinking
- 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 8B Thinking
Particle-1 outperforms in 2 benchmarks (GPQA, MMLU), while Qwen3 VL 8B Thinking is better at 0 benchmarks.
Particle-1 significantly outperforms across most 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 1.4x more expensive than Qwen3 VL 8B Thinking ($0.18/1M tokens).
For output processing, Particle-1 ($1.00/1M tokens) is 2.1x cheaper than Qwen3 VL 8B Thinking ($2.09/1M tokens).
In conclusion, Qwen3 VL 8B Thinking is more expensive than Particle-1.*
* 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 8B Thinking's 262,144 tokens. Qwen3 VL 8B Thinking can generate longer responses up to 262,144 tokens, while Particle-1 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both Particle-1 and Qwen3 VL 8B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Particle-1
Qwen3 VL 8B Thinking
License
Usage and distribution terms
Particle-1 is licensed under a proprietary license, while Qwen3 VL 8B 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 8B Thinking was released on 2025-09-22.
Particle-1 is 13 months newer than Qwen3 VL 8B 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 8B Thinking is available from DeepInfra.
Particle-1
Qwen3 VL 8B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Particle-1 and Qwen3 VL 8B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Particle-1 vs Qwen3 VL 8B Thinking.