DeepSeek-V3 0324 vs Particle-1
Particle-1 leads the LLM Stats Score 31.9 to 12.8. DeepSeek-V3 0324 is 1.1x cheaper per token.
DeepSeek · Particle AI · Updated for 2026
Which is better?
Particle-1 leads the overall LLM Stats Score 31.9 to 12.8, ranking #133 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, DeepSeek-V3 0324 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 DeepSeek-V3 0324
- cost matters — it's about 1.1x cheaper per token
- you need open weights you can self-host or fine-tune
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 1 of 1 exact shared results
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
5 reported for DeepSeek-V3 0324 · 3 for Particle-1
DeepSeek-V3 0324 outperforms in 0 benchmarks, while Particle-1 is better at 1 benchmark (GPQA).
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, DeepSeek-V3 0324 ($0.24/1M tokens) is 1.0x cheaper than Particle-1 ($0.25/1M tokens).
For output processing, DeepSeek-V3 0324 ($0.90/1M tokens) is 1.1x cheaper than Particle-1 ($1.00/1M tokens).
In conclusion, Particle-1 is more expensive than DeepSeek-V3 0324.*
* 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 DeepSeek-V3 0324's 163,840 tokens. DeepSeek-V3 0324 can generate longer responses up to 163,840 tokens, while Particle-1 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Particle-1 supports multimodal inputs, whereas DeepSeek-V3 0324 does not.
Particle-1 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3 0324
Particle-1
License
Usage and distribution terms
DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), while Particle-1 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT + Model License (Commercial use allowed)
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V3 0324 was released on 2025-03-25, while Particle-1 was released on 2026-10-28.
Particle-1 is 19 months newer than DeepSeek-V3 0324.
Mar 25, 2025
1.6 years ago
Oct 28, 2026
-1 days ago
1.6yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V3 0324 is available from DeepInfra, Novita. Particle-1 is available from Particle AI.
DeepSeek-V3 0324
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3 0324 and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 0324 vs Particle-1.