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DeepSeek-V4-Pro-0813 vs Hy3

DeepSeek-V4-Pro-0813 leads the LLM Stats Score 54.1 to 42.9.

DeepSeek · Tencent · Updated for 2026

Which is better?

DeepSeek-V4-Pro-0813 leads the overall LLM Stats Score 54.1 to 42.9, ranking #7 overall.

In the 6 individual benchmarks reported for both models, DeepSeek-V4-Pro-0813 wins 5; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V4-Pro-0813

  • overall performance matters — it scores 54.1 and ranks #7 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 5 of 6 exact shared results
  • you want the most recent training data — it shipped Aug 2026

Choose Hy3

  • you are already invested in the Tencent ecosystem

At a glance

The differences that matter most.

Core performance indexes
54.1
#7
42.9
#39
51.5
#8
42.9
#37
44.2
#7
35.0
#27
40.4
#7
28.2
#36
Cost, coverage & limits
Benchmark wins
5 of 6
1 of 6
Input price
$0.43 / M
— / M
Output price
$0.87 / M
— / M
Context window
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4-Pro-0813
Hy3
41.8#6
34.6#43
33.6#6
23.2#39
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

12 reported for DeepSeek-V4-Pro-0813 · 31 for Hy3

6 shared

DeepSeek-V4-Pro-0813 outperforms in 5 benchmarks (DeepSWE, Humanity's Last Exam (with tools, text-only), NL2Repo, Terminal-Bench 2.1, Toolathlon), while Hy3 is better at 1 benchmark (Humanity's Last Exam (no tools, text-only)).

DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks.

Fri Aug 28 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

1305.0B diff

DeepSeek-V4-Pro-0813 has 1305.0B more parameters than Hy3, making it 442.4% larger.

DeepSeek
DeepSeek-V4-Pro-0813
1.6Tparameters
Tencent
Hy3
295.0Bparameters
1600.0B
DeepSeek-V4-Pro-0813
295.0B
Hy3

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Pro-0813 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Pro-0813 specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4-Pro-0813
Input1,048,576 tokens
Output393,216 tokens
Tencent
Hy3
Input- tokens
Output- tokens
Fri Aug 28 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V4-Pro-0813 is licensed under MIT, while Hy3 uses Apache 2.0.

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

DeepSeek-V4-Pro-0813

MIT

Open weights

Hy3

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Hy3 was released on 2026-07-06.

DeepSeek-V4-Pro-0813 is 1 month newer than Hy3.

DeepSeek-V4-Pro-0813

Aug 13, 2026

2 weeks ago

1mo newer
Hy3

Jul 6, 2026

1 months ago

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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek-V4-Pro-0813 and Hy3 side-by-side, then vote on the output you prefer.

DeepSeek-V4-Pro-0813
✓ Preferred
Hy3
Open in Playground

FAQ

Common questions about DeepSeek-V4-Pro-0813 vs Hy3.

Which is better, DeepSeek-V4-Pro-0813 or Hy3?

DeepSeek-V4-Pro-0813 leads the LLM Stats Score 54.1 to 42.9. DeepSeek-V4-Pro-0813 is made by DeepSeek and Hy3 is made by Tencent. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4-Pro-0813 compare to Hy3 in benchmarks?

DeepSeek-V4-Pro-0813 scores Terminal-Bench 2.1: 87.9%, CyberGym: 83.3%, Toolathlon: 74.1%, DSBench-FullStack: 71.1%, DSBench-Hard: 67.2%. Hy3 scores DeepSearchQA: 91.0%, GPQA: 90.4%, IMO-AnswerBench: 90.0%, BrowseComp: 84.2%, MCP Atlas: 79.1%.

What are the context window sizes for DeepSeek-V4-Pro-0813 and Hy3?

DeepSeek-V4-Pro-0813 supports 1.0M tokens and Hy3 supports an unknown number of 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-Pro-0813 and Hy3?

Key differences include LLM Stats Score (54.1 vs 42.9), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Pro-0813 and Hy3?

DeepSeek-V4-Pro-0813 is developed by DeepSeek and Hy3 is developed by Tencent.