DeepSeek-V4-Pro-Max vs DeepSeek-V4.1-Flash-1017
DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 42.9. DeepSeek-V4.1-Flash-1017 is 3.1x cheaper per token.
DeepSeek · DeepSeek · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 42.9, ranking #15 overall.
In the 1 individual benchmarks reported for both models, DeepSeek-V4-Pro-Max wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4.1-Flash-1017 is roughly 3.1x 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
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
Choose DeepSeek-V4.1-Flash-1017
- overall performance matters — it scores 51.0 and ranks #15 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 3.1x cheaper per token
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
22 reported for DeepSeek-V4-Pro-Max · 11 for DeepSeek-V4.1-Flash-1017
DeepSeek-V4-Pro-Max outperforms in 1 benchmarks (Humanity's Last Exam), while DeepSeek-V4.1-Flash-1017 is better at 0 benchmarks.
DeepSeek-V4-Pro-Max 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 4.3x more expensive than DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens).
For output processing, DeepSeek-V4-Pro-Max ($2.60/1M tokens) is 2.2x more expensive than DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens).
In conclusion, DeepSeek-V4-Pro-Max is more expensive than DeepSeek-V4.1-Flash-1017.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Pro-Max has 836.8B more parameters than DeepSeek-V4.1-Flash-1017, making it 109.6% larger.
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 DeepSeek-V4.1-Flash-1017 is limited to 393,216 tokens.
Input capabilities
Documented input modalities across available providers
DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas DeepSeek-V4-Pro-Max does not.
DeepSeek-V4.1-Flash-1017 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-Max
DeepSeek-V4.1-Flash-1017
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-V4-Pro-Max was released on 2026-04-23, while DeepSeek-V4.1-Flash-1017 was released on 2026-10-17.
DeepSeek-V4.1-Flash-1017 is 6 months newer than DeepSeek-V4-Pro-Max.
Apr 23, 2026
5 months ago
Oct 17, 2026
2 days ago
5mo 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. DeepSeek-V4.1-Flash-1017 is available from DeepSeek.
DeepSeek-V4-Pro-Max
DeepSeek-V4.1-Flash-1017
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-Max and DeepSeek-V4.1-Flash-1017 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-Max vs DeepSeek-V4.1-Flash-1017.
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