DeepSeek-V3 vs Mercury 3

Mercury 3 leads the LLM Stats Score 36.1 to 15.1. Mercury 3 is 2.6x cheaper per token.

DeepSeek · Inception · Updated for 2026

Which is better?

Mercury 3 leads the overall LLM Stats Score 36.1 to 15.1, ranking #98 overall.

In the 1 individual benchmarks reported for both models, Mercury 3 wins 1; this is a narrower head-to-head signal than the composite indexes.

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

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-V3

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 and coding — it leads those capability indexes
you value its reported benchmark strengths — it wins 1 of 1 exact shared results
cost matters — it's about 2.6x cheaper per token
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.

Better token value: Mercury 3

Core performance indexes

LLM Stats Score

15.1

#254 · 19 evals

36.1

#98 · 10 evals

Best

Reasoning

14.3

#253 · 14 evals

34.8

#103 · 8 evals

Best

Coding

5.9

#215 · 4 evals

21.5

#105 · 1 evals

Best

Cost, coverage & limits

Benchmark wins

0 of 1

1 of 1

Best

Input price

$0.27 / M

$0.10 / M

Best

Output price

$0.89 / M

$0.35 / M

Best

Context window

131,072

1,000,000

Best

Individual benchmarks

20 reported for DeepSeek-V3 · 12 for Mercury 3

1 shared

DeepSeek-V3 outperforms in 0 benchmarks, while Mercury 3 is better at 1 benchmark (GPQA).

Mercury 3 significantly outperforms across most benchmarks.

Thu Oct 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Mercury 3 costs less

For input processing, DeepSeek-V3 ($0.27/1M tokens) is 2.7x more expensive than Mercury 3 ($0.10/1M tokens).

For output processing, DeepSeek-V3 ($0.89/1M tokens) is 2.5x more expensive than Mercury 3 ($0.35/1M tokens).

In conclusion, DeepSeek-V3 is more expensive than Mercury 3.*

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

Lowest available price from all providers

Thu Oct 22 2026 • llm-stats.com

DeepSeek-V3

Input tokens$0.27

Output tokens$0.89

Best providerDeepSeek

Mercury 3

Input tokens$0.10

Output tokens$0.35

Best providerInception

Notice missing or incorrect data?

Context Window

Maximum input and output token capacity

Mercury 3 accepts 1,000,000 input tokens compared to DeepSeek-V3's 131,072 tokens. Both models can generate responses up to 131,072 tokens.

DeepSeek-V3

Input131,072 tokens

Output131,072 tokens

Mercury 3

Input1,000,000 tokens

Output131,072 tokens

Thu Oct 22 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Mercury 3 uses a proprietary license.

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Mercury 3

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Mercury 3 was released on 2026-10-19.

Mercury 3 is 22 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.8 years ago

Mercury 3

Oct 19, 2026

0 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-V3 is available from DeepSeek, DeepInfra. Mercury 3 is available from Inception.

DeepSeek-V3

DeepSeek

Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

Deepinfra

Input Price:Input: $0.32/1MOutput Price:Output: $0.89/1M

Mercury 3

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-V3 and Mercury 3 side-by-side, then vote on the output you prefer.

DeepSeek-V3

✓ Preferred

Mercury 3

Open in Playground

FAQ

Common questions about DeepSeek-V3 vs Mercury 3.

Which is better, DeepSeek-V3 or Mercury 3?

Mercury 3 leads the LLM Stats Score 36.1 to 15.1. DeepSeek-V3 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-V3 compare to Mercury 3 in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Mercury 3 scores GPQA: 89.2%, AA-LCR: 77.7%, IFBench: 76.8%, MRCR v2: 75.5%, DeepSearchQA: 71.3%.

Is DeepSeek-V3 cheaper than Mercury 3?

Mercury 3 is 2.7x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $0.89/M output via deepseek. Mercury 3 costs $0.10/M input and $0.35/M output via inception.

What are the context window sizes for DeepSeek-V3 and Mercury 3?

DeepSeek-V3 supports 131K 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-V3 and Mercury 3?

Key differences include LLM Stats Score (15.1 vs 36.1), context window (131K vs 1.0M), input pricing ($0.27 vs $0.10/M), licensing (MIT + Model License (Commercial use allowed) vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 and Mercury 3?

DeepSeek-V3 is developed by DeepSeek and Mercury 3 is developed by Inception.

DeepSeek-V3 vs Mercury 3