DeepSeek-V4.1-Flash vs Particle-1
DeepSeek-V4.1-Flash leads the LLM Stats Score 49.5 to 32.0. DeepSeek-V4.1-Flash is 1.3x cheaper per token.
DeepSeek · Particle AI · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash leads the overall LLM Stats Score 49.5 to 32.0, ranking #24 overall.
In the 2 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4.1-Flash is roughly 1.3x 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-V4.1-Flash
- overall performance matters — it scores 49.5 and ranks #24 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 1.3x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Particle-1
- 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
20 reported for DeepSeek-V4.1-Flash · 3 for Particle-1
DeepSeek-V4.1-Flash outperforms in 2 benchmarks (BabyVision, GPQA), while Particle-1 is better at 0 benchmarks.
DeepSeek-V4.1-Flash 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 ($0.22/1M tokens) is 1.1x cheaper than Particle-1 ($0.25/1M tokens).
For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 1.5x cheaper than Particle-1 ($1.00/1M tokens).
In conclusion, Particle-1 is more expensive than DeepSeek-V4.1-Flash.*
* 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-V4.1-Flash's 1,040,000 tokens. DeepSeek-V4.1-Flash 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 and Particle-1 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4.1-Flash
Particle-1
License
Usage and distribution terms
DeepSeek-V4.1-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
DeepSeek-V4.1-Flash was released on 2026-09-10, while Particle-1 was released on 2026-10-28.
Particle-1 is 2 months newer than DeepSeek-V4.1-Flash.
Sep 10, 2026
1 months ago
Oct 28, 2026
1 weeks ago
1mo 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 is available from Fireworks, DeepInfra, Novita. Particle-1 is available from Particle AI.
DeepSeek-V4.1-Flash
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash vs Particle-1.