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DeepSeek-V4-Flash-Vision-Exp vs Gemini 2.0 Flash-Lite

Comparing DeepSeek-V4-Flash-Vision-Exp and Gemini 2.0 Flash-Lite across benchmarks, pricing, and capabilities.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek-V4-Flash-Vision-Exp and Gemini 2.0 Flash-Lite trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

On price, Gemini 2.0 Flash-Lite is roughly 2.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek-V4-Flash-Vision-Exp

  • you want the most recent training data — it shipped Aug 2026

Choose Gemini 2.0 Flash-Lite

  • cost matters — it's about 2.6x cheaper per token

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.22 / M
$0.07 / M
Output price
$0.66 / M
$0.30 / M
Context window
1,048,576
1,048,576
Released
Aug 2026
Feb 2025
License
Unknown
Proprietary

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V4-Flash-Vision-Exp and Gemini 2.0 Flash-Litedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Pricing Analysis

Price comparison per million tokens

Gemini 2.0 Flash-Lite costs less

For input processing, DeepSeek-V4-Flash-Vision-Exp ($0.22/1M tokens) is 3.1x more expensive than Gemini 2.0 Flash-Lite ($0.07/1M tokens).

For output processing, DeepSeek-V4-Flash-Vision-Exp ($0.66/1M tokens) is 2.2x more expensive than Gemini 2.0 Flash-Lite ($0.30/1M tokens).

In conclusion, DeepSeek-V4-Flash-Vision-Exp is more expensive than Gemini 2.0 Flash-Lite.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Mon Aug 24 2026 • llm-stats.com
DeepSeek
DeepSeek-V4-Flash-Vision-Exp
Input tokens$0.22
Output tokens$0.66
Best providerDeepSeek
Google
Gemini 2.0 Flash-Lite
Input tokens$0.07
Output tokens$0.30
Best providerGoogle
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

Both models have the same input context window of 1,048,576 tokens. DeepSeek-V4-Flash-Vision-Exp can generate longer responses up to 393,216 tokens, while Gemini 2.0 Flash-Lite is limited to 8,192 tokens.

DeepSeek
DeepSeek-V4-Flash-Vision-Exp
Input1,048,576 tokens
Output393,216 tokens
Google
Gemini 2.0 Flash-Lite
Input1,048,576 tokens
Output8,192 tokens
Mon Aug 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DeepSeek-V4-Flash-Vision-Exp and Gemini 2.0 Flash-Lite support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek-V4-Flash-Vision-Exp

Text
Images
Audio
Video

Gemini 2.0 Flash-Lite

Text
Images
Audio
Video

Release Timeline

When each model was launched

DeepSeek-V4-Flash-Vision-Exp was released on 2026-08-21, while Gemini 2.0 Flash-Lite was released on 2025-02-05.

DeepSeek-V4-Flash-Vision-Exp is 19 months newer than Gemini 2.0 Flash-Lite.

DeepSeek-V4-Flash-Vision-Exp

Aug 21, 2026

3 days ago

1.5yr newer
Gemini 2.0 Flash-Lite

Feb 5, 2025

1.5 years ago

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash-Lite has a documented knowledge cutoff of 2024-06-01, while DeepSeek-V4-Flash-Vision-Exp's cutoff date is not specified.

We can confirm Gemini 2.0 Flash-Lite's training data extends to 2024-06-01, but cannot make a direct comparison without DeepSeek-V4-Flash-Vision-Exp's cutoff date.

DeepSeek-V4-Flash-Vision-Exp

Gemini 2.0 Flash-Lite

Jun 2024

Provider Availability

DeepSeek-V4-Flash-Vision-Exp is available from DeepSeek. Gemini 2.0 Flash-Lite is available from Google.

DeepSeek-V4-Flash-Vision-Exp

deepseek logo
DeepSeek
Input Price:Input: $0.22/1MOutput Price:Output: $0.66/1M

Gemini 2.0 Flash-Lite

google logo
Google
Input Price:Input: $0.07/1MOutput Price:Output: $0.30/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek-V4-Flash-Vision-Exp and Gemini 2.0 Flash-Lite side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-Vision-Exp
✓ Preferred
Gemini 2.0 Flash-Lite
Open in Playground

FAQ

Common questions about DeepSeek-V4-Flash-Vision-Exp vs Gemini 2.0 Flash-Lite.

Which is better, DeepSeek-V4-Flash-Vision-Exp or Gemini 2.0 Flash-Lite?

DeepSeek-V4-Flash-Vision-Exp (DeepSeek) and Gemini 2.0 Flash-Lite (Google) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-V4-Flash-Vision-Exp compare to Gemini 2.0 Flash-Lite in benchmarks?

DeepSeek-V4-Flash-Vision-Exp scores Terminal-Bench 2.1: 83.9%, DSBench-Hard: 63.6%, DeepSWE: 59.3%, NL2Repo: 57.7%, ZEROBench: 35.0%. Gemini 2.0 Flash-Lite scores MATH: 86.8%, FACTS Grounding: 83.6%, Global-MMLU-Lite: 78.2%, MMLU-Pro: 71.6%, MMMU: 68.0%.

Is DeepSeek-V4-Flash-Vision-Exp cheaper than Gemini 2.0 Flash-Lite?

Gemini 2.0 Flash-Lite is 3.1x cheaper for input tokens. DeepSeek-V4-Flash-Vision-Exp costs $0.22/M input and $0.66/M output via deepseek. Gemini 2.0 Flash-Lite costs $0.07/M input and $0.30/M output via google.

What are the context window sizes for DeepSeek-V4-Flash-Vision-Exp and Gemini 2.0 Flash-Lite?

DeepSeek-V4-Flash-Vision-Exp supports 1.0M tokens and Gemini 2.0 Flash-Lite supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4-Flash-Vision-Exp and Gemini 2.0 Flash-Lite?

Key differences include input pricing ($0.22 vs $0.07/M), licensing (Unknown vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-Vision-Exp and Gemini 2.0 Flash-Lite?

DeepSeek-V4-Flash-Vision-Exp is developed by DeepSeek and Gemini 2.0 Flash-Lite is developed by Google.