DeepSeek-V4.1-Flash vs Gemini 1.5 Flash
DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 6.0. Gemini 1.5 Flash is 2.0x cheaper per token.
DeepSeek · Google · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 6.0, ranking #12 overall.
In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Gemini 1.5 Flash is roughly 2.0x 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
- 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 1 of 1 exact shared results
- you want the most recent training data — it shipped Sep 2026
- you need open weights you can self-host or fine-tune
Choose Gemini 1.5 Flash
- cost matters — it's about 2.0x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for DeepSeek-V4.1-Flash · 22 for Gemini 1.5 Flash
DeepSeek-V4.1-Flash outperforms in 1 benchmarks (GPQA), while Gemini 1.5 Flash 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 ($0.30/1M tokens) is 2.0x more expensive than Gemini 1.5 Flash ($0.15/1M tokens).
For output processing, DeepSeek-V4.1-Flash ($1.20/1M tokens) is 2.0x more expensive than Gemini 1.5 Flash ($0.60/1M tokens).
In conclusion, DeepSeek-V4.1-Flash is more expensive than Gemini 1.5 Flash.*
* 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 can generate longer responses up to 393,216 tokens, while Gemini 1.5 Flash is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Both DeepSeek-V4.1-Flash and Gemini 1.5 Flash support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4.1-Flash
Gemini 1.5 Flash
License
Usage and distribution terms
DeepSeek-V4.1-Flash is licensed under MIT, while Gemini 1.5 Flash 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 Gemini 1.5 Flash was released on 2024-05-01.
DeepSeek-V4.1-Flash is 29 months newer than Gemini 1.5 Flash.
Sep 10, 2026
0 days ago
2.4yr newerMay 1, 2024
2.4 years ago
Knowledge Cutoff
When training data ends
Gemini 1.5 Flash has a documented knowledge cutoff of 2023-11-01, while DeepSeek-V4.1-Flash's cutoff date is not specified.
We can confirm Gemini 1.5 Flash's training data extends to 2023-11-01, but cannot make a direct comparison without DeepSeek-V4.1-Flash's cutoff date.
—
Nov 2023
Provider Availability
DeepSeek-V4.1-Flash is available from DeepSeek. Gemini 1.5 Flash is available from Google.
DeepSeek-V4.1-Flash
Gemini 1.5 Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash and Gemini 1.5 Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash vs Gemini 1.5 Flash.