The AI arena is free today

Open Superagent

DeepSeek VL2 vs Mercury 3

Mercury 3 leads the LLM Stats Score 36.1 to 2.5.

DeepSeek · Inception · Updated for 2026

Which is better?

Mercury 3 leads the overall LLM Stats Score 36.1 to 2.5, ranking #98 overall.

Mercury 3 also accepts a larger context window (1,000,000 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 VL2

  • you need open weights you can self-host or fine-tune

Choose Mercury 3

  • overall performance matters — it scores 36.1 and ranks #98 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you process long inputs — it offers a 1,000,000 token context window
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

Core performance indexes
2.5
#337
36.1
#98
-2.3
#355
34.8
#103
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.10 / M
Output price
— / M
$0.35 / M
Context window
129,280
1,000,000

Individual benchmarks

14 reported for DeepSeek VL2 · 12 for Mercury 3

No common benchmarks found

DeepSeek VL2 and Mercury 3don'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

Context Window

Maximum input and output token capacity

Mercury 3 accepts 1,000,000 input tokens compared to DeepSeek VL2's 129,280 tokens. Mercury 3 can generate longer responses up to 131,072 tokens, while DeepSeek VL2 is limited to 129,280 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Inception
Mercury 3
Input1,000,000 tokens
Output131,072 tokens
Fri Oct 23 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek VL2 supports multimodal inputs, whereas Mercury 3 does not.

DeepSeek VL2 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek VL2

Text
Images
Audio
Video

Mercury 3

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while Mercury 3 uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek VL2

deepseek

Open weights

Mercury 3

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Mercury 3 was released on 2026-10-19.

Mercury 3 is 23 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.9 years ago

Mercury 3

Oct 19, 2026

3 days ago

1.8yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek VL2 is available from Replicate. Mercury 3 is available from Inception.

DeepSeek VL2

replicate logo
Replicate

Mercury 3

inception logo
Inception
Input Price:Input: $0.10/1MOutput Price:Output: $0.35/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek VL2 and Mercury 3 side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
Mercury 3
Open in Playground

FAQ

Common questions about DeepSeek VL2 vs Mercury 3.

Which is better, DeepSeek VL2 or Mercury 3?

Mercury 3 leads the LLM Stats Score 36.1 to 2.5. DeepSeek VL2 is made by DeepSeek and Mercury 3 is made by Inception. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek VL2 compare to Mercury 3 in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. Mercury 3 scores GPQA: 89.2%, AA-LCR: 77.7%, IFBench: 76.8%, MRCR v2: 75.5%, DeepSearchQA: 71.3%.

What are the context window sizes for DeepSeek VL2 and Mercury 3?

DeepSeek VL2 supports 129K tokens and Mercury 3 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 VL2 and Mercury 3?

Key differences include LLM Stats Score (2.5 vs 36.1), context window (129K vs 1.0M), multimodal support (yes vs no), licensing (deepseek vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 and Mercury 3?

DeepSeek VL2 is developed by DeepSeek and Mercury 3 is developed by Inception.