DeepSeek-V4.1-Flash-1017 vs Particle-1
DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 50.7 to 31.9. Particle-1 is 1.2x cheaper per token.
DeepSeek · Particle AI · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 50.7 to 31.9, ranking #17 overall.
In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash-1017 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Particle-1 is roughly 1.2x 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-V4.1-Flash-1017
- overall performance matters — it scores 50.7 and ranks #17 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 need open weights you can self-host or fine-tune
Choose Particle-1
- cost matters — it's about 1.2x cheaper per token
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
11 reported for DeepSeek-V4.1-Flash-1017 · 3 for Particle-1
DeepSeek-V4.1-Flash-1017 outperforms in 1 benchmarks (BabyVision), while Particle-1 is better at 0 benchmarks.
DeepSeek-V4.1-Flash-1017 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-V4.1-Flash-1017 ($0.30/1M tokens) is 1.2x more expensive than Particle-1 ($0.25/1M tokens).
For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 1.2x more expensive than Particle-1 ($1.00/1M tokens).
In conclusion, DeepSeek-V4.1-Flash-1017 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-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while Particle-1 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both DeepSeek-V4.1-Flash-1017 and Particle-1 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4.1-Flash-1017
Particle-1
License
Usage and distribution terms
DeepSeek-V4.1-Flash-1017 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-V4.1-Flash-1017 was released on 2026-10-17, while Particle-1 was released on 2026-10-28.
Particle-1 is 0 month newer than DeepSeek-V4.1-Flash-1017.
Oct 17, 2026
1 weeks ago
Oct 28, 2026
-1 days ago
1w 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-V4.1-Flash-1017 is available from DeepSeek. Particle-1 is available from Particle AI.
DeepSeek-V4.1-Flash-1017
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash-1017 and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash-1017 vs Particle-1.