DeepSeek-R1 vs Particle-1
Comparing DeepSeek-R1 and Particle-1 across benchmarks, pricing, and capabilities.
DeepSeek · Particle AI · Updated for 2026
Which is better?
DeepSeek-R1 and Particle-1 trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Particle-1 is roughly 2.2x 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-R1
- you need open weights you can self-host or fine-tune
Choose Particle-1
- cost matters — it's about 2.2x 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
At a glance
The differences that matter most.
Individual benchmarks
0 reported for DeepSeek-R1 · 3 for Particle-1
DeepSeek-R1 and Particle-1don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1 ($0.55/1M tokens) is 2.2x more expensive than Particle-1 ($0.25/1M tokens).
For output processing, DeepSeek-R1 ($2.19/1M tokens) is 2.2x more expensive than Particle-1 ($1.00/1M tokens).
In conclusion, DeepSeek-R1 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 DeepSeek-R1's 131,072 tokens. Both models can generate responses up to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Particle-1 supports multimodal inputs, whereas DeepSeek-R1 does not.
Particle-1 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1
Particle-1
License
Usage and distribution terms
DeepSeek-R1 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
DeepSeek-R1 was released on 2025-01-20, while Particle-1 was released on 2026-10-28.
Particle-1 is 22 months newer than DeepSeek-R1.
Jan 20, 2025
1.8 years ago
Oct 28, 2026
1 days ago
1.8yr 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-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Particle-1 is available from Particle AI.
DeepSeek-R1
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1 and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1 vs Particle-1.