GLM-5.3-Flash vs Particle-1
GLM-5.3-Flash leads the LLM Stats Score 48.3 to 32.0. GLM-5.3-Flash is 1.8x cheaper per token.
Zhipu AI · Particle AI · Updated for 2026
Which is better?
GLM-5.3-Flash leads the overall LLM Stats Score 48.3 to 32.0, ranking #32 overall.
In the 1 individual benchmarks reported for both models, Particle-1 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-5.3-Flash is roughly 1.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GLM-5.3-Flash
- overall performance matters — it scores 48.3 and ranks #32 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 1.8x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Particle-1
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
15 reported for GLM-5.3-Flash · 3 for Particle-1
GLM-5.3-Flash outperforms in 0 benchmarks, while Particle-1 is better at 1 benchmark (BabyVision).
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, GLM-5.3-Flash ($0.15/1M tokens) is 1.7x cheaper than Particle-1 ($0.25/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 2.0x cheaper than Particle-1 ($1.00/1M tokens).
In conclusion, Particle-1 is more expensive than GLM-5.3-Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. GLM-5.3-Flash can generate longer responses up to 1,048,576 tokens, while Particle-1 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both GLM-5.3-Flash and Particle-1 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GLM-5.3-Flash
Particle-1
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while Particle-1 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while Particle-1 was released on 2026-10-28.
Particle-1 is 2 months newer than GLM-5.3-Flash.
Aug 26, 2026
2 months ago
Oct 28, 2026
1 weeks ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-5.3-Flash is available from DeepInfra, FriendliAI, Novita, ZAI. Particle-1 is available from Particle AI.
GLM-5.3-Flash
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Particle-1.