DeepSeek-V4-Pro-Max vs Particle-1
DeepSeek-V4-Pro-Max and Particle-1 are closely matched at 42.6 and 32.0 on the LLM Stats Score. Particle-1 is 3.7x cheaper per token.
DeepSeek · Particle AI · Updated for 2026
Which is better?
DeepSeek-V4-Pro-Max and Particle-1 are closely matched on the overall LLM Stats Score at 42.6 and 32.0.
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, Particle-1 is roughly 3.7x 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 DeepSeek-V4-Pro-Max
- your work emphasizes reasoning — it leads those capability indexes
- 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
- cost matters — it's about 3.7x cheaper per token
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
22 reported for DeepSeek-V4-Pro-Max · 3 for Particle-1
DeepSeek-V4-Pro-Max 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-V4-Pro-Max ($1.30/1M tokens) is 5.2x more expensive than Particle-1 ($0.25/1M tokens).
For output processing, DeepSeek-V4-Pro-Max ($2.60/1M tokens) is 2.6x more expensive than Particle-1 ($1.00/1M tokens).
In conclusion, DeepSeek-V4-Pro-Max is more expensive than Particle-1.*
* 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. DeepSeek-V4-Pro-Max 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
Particle-1 supports multimodal inputs, whereas DeepSeek-V4-Pro-Max does not.
Particle-1 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-Max
Particle-1
License
Usage and distribution terms
DeepSeek-V4-Pro-Max 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-V4-Pro-Max was released on 2026-04-23, while Particle-1 was released on 2026-10-28.
Particle-1 is 6 months newer than DeepSeek-V4-Pro-Max.
Apr 23, 2026
6 months ago
Oct 28, 2026
3 days ago
6mo 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-V4-Pro-Max is available from DeepInfra, Novita, DeepSeek, Fireworks, Together. Particle-1 is available from Particle AI.
DeepSeek-V4-Pro-Max
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-Max and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-Max vs Particle-1.