DeepSeek-R1-0528 vs DeepSeek-V4.1-Flash
DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 24.1. DeepSeek-V4.1-Flash is 2.8x cheaper per token.
DeepSeek · DeepSeek · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 24.1, ranking #12 overall.
In the 3 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4.1-Flash is roughly 2.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4.1-Flash also accepts a larger context window (1,040,000 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-R1-0528
- you want predictable pricing at $0.50/M input and $2.15/M output
Choose DeepSeek-V4.1-Flash
- overall performance matters — it scores 51.8 and ranks #12 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- cost matters — it's about 2.8x cheaper per token
- you process long inputs — it offers a 1,040,000 token context window
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
16 reported for DeepSeek-R1-0528 · 20 for DeepSeek-V4.1-Flash
DeepSeek-R1-0528 outperforms in 0 benchmarks, while DeepSeek-V4.1-Flash is better at 3 benchmarks (CodeForces, GPQA, Humanity's Last Exam).
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-R1-0528 ($0.50/1M tokens) is 2.3x more expensive than DeepSeek-V4.1-Flash ($0.22/1M tokens).
For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 3.3x more expensive than DeepSeek-V4.1-Flash ($0.66/1M tokens).
In conclusion, DeepSeek-R1-0528 is more expensive than DeepSeek-V4.1-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4.1-Flash has 92.2B more parameters than DeepSeek-R1-0528, making it 13.7% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to DeepSeek-R1-0528's 163,840 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while DeepSeek-R1-0528 is limited to 163,840 tokens.
Input capabilities
Documented input modalities across available providers
DeepSeek-V4.1-Flash supports multimodal inputs, whereas DeepSeek-R1-0528 does not.
DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1-0528
DeepSeek-V4.1-Flash
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek-R1-0528 was released on 2025-05-28, while DeepSeek-V4.1-Flash was released on 2026-09-10.
DeepSeek-V4.1-Flash is 16 months newer than DeepSeek-R1-0528.
May 28, 2025
1.3 years ago
Sep 10, 2026
3 days ago
1.3yr 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-R1-0528 is available from DeepInfra, DeepSeek, Novita. DeepSeek-V4.1-Flash is available from Fireworks, DeepInfra, DeepSeek, Novita.
DeepSeek-R1-0528
DeepSeek-V4.1-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1-0528 and DeepSeek-V4.1-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1-0528 vs DeepSeek-V4.1-Flash.