DeepSeek-V4-Flash-0731 vs Gemini 1.0 Pro
DeepSeek-V4-Flash-0731 leads the LLM Stats Score 44.7 to -5.4. DeepSeek-V4-Flash-0731 is 8.3x cheaper per token.
DeepSeek · Google · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0731 leads the overall LLM Stats Score 44.7 to -5.4, ranking #35 overall.
On price, DeepSeek-V4-Flash-0731 is roughly 8.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-0731 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-Flash-0731
- overall performance matters — it scores 44.7 and ranks #35 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 8.3x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 2026
- you need open weights you can self-host or fine-tune
Choose Gemini 1.0 Pro
- you want predictable pricing at $0.50/M input and $1.50/M output
At a glance
The differences that matter most.
Individual benchmarks
9 reported for DeepSeek-V4-Flash-0731 · 9 for Gemini 1.0 Pro
DeepSeek-V4-Flash-0731 and Gemini 1.0 Prodon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.06/1M tokens) is 8.3x cheaper than Gemini 1.0 Pro ($0.50/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 8.3x cheaper than Gemini 1.0 Pro ($1.50/1M tokens).
In conclusion, Gemini 1.0 Pro is more expensive than DeepSeek-V4-Flash-0731.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0731 accepts 1,048,576 input tokens compared to Gemini 1.0 Pro's 32,760 tokens. DeepSeek-V4-Flash-0731 can generate longer responses up to 1,048,576 tokens, while Gemini 1.0 Pro is limited to 8,192 tokens.
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 is licensed under MIT, while Gemini 1.0 Pro 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-Flash-0731 was released on 2026-07-31, while Gemini 1.0 Pro was released on 2024-02-15.
DeepSeek-V4-Flash-0731 is 30 months newer than Gemini 1.0 Pro.
Jul 31, 2026
1 months ago
2.5yr newerFeb 15, 2024
2.6 years ago
Knowledge Cutoff
When training data ends
Gemini 1.0 Pro has a documented knowledge cutoff of 2024-02-01, while DeepSeek-V4-Flash-0731's cutoff date is not specified.
We can confirm Gemini 1.0 Pro's training data extends to 2024-02-01, but cannot make a direct comparison without DeepSeek-V4-Flash-0731's cutoff date.
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Feb 2024
Provider Availability
DeepSeek-V4-Flash-0731 is available from DeepInfra, Novita, Fireworks. Gemini 1.0 Pro is available from Google.
DeepSeek-V4-Flash-0731
Gemini 1.0 Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and Gemini 1.0 Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Gemini 1.0 Pro.