DeepSeek-V3.2-Exp vs DeepSeek-V4.1-Flash
DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 28.2. DeepSeek-V3.2-Exp is 1.1x cheaper per token.
DeepSeek · DeepSeek · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 28.2, ranking #13 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-V3.2-Exp is roughly 1.1x 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-V3.2-Exp
- cost matters — it's about 1.1x cheaper per token
Choose DeepSeek-V4.1-Flash
- overall performance matters — it scores 51.8 and ranks #13 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
- 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
14 reported for DeepSeek-V3.2-Exp · 20 for DeepSeek-V4.1-Flash
DeepSeek-V3.2-Exp 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-V3.2-Exp ($0.27/1M tokens) is 1.2x more expensive than DeepSeek-V4.1-Flash ($0.22/1M tokens).
For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 1.6x cheaper than DeepSeek-V4.1-Flash ($0.66/1M tokens).
In conclusion, DeepSeek-V4.1-Flash is more expensive than DeepSeek-V3.2-Exp.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4.1-Flash has 78.2B more parameters than DeepSeek-V3.2-Exp, making it 11.4% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to DeepSeek-V3.2-Exp's 163,840 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while DeepSeek-V3.2-Exp is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
DeepSeek-V4.1-Flash supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.
DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3.2-Exp
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-V3.2-Exp was released on 2025-09-29, while DeepSeek-V4.1-Flash was released on 2026-09-10.
DeepSeek-V4.1-Flash is 12 months newer than DeepSeek-V3.2-Exp.
Sep 29, 2025
11 months ago
Sep 10, 2026
1 weeks ago
11mo 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-V3.2-Exp is available from Novita. DeepSeek-V4.1-Flash is available from Fireworks, DeepInfra, DeepSeek, Novita.
DeepSeek-V3.2-Exp
DeepSeek-V4.1-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.2-Exp and DeepSeek-V4.1-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.2-Exp vs DeepSeek-V4.1-Flash.