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DeepSeek-V4-Pro-0813 vs IBM Granite 4.2 30B

DeepSeek-V4-Pro-0813 leads the LLM Stats Score 52.9 to 24.0.

DeepSeek · IBM · Updated for 2026

Which is better?

DeepSeek-V4-Pro-0813 leads the overall LLM Stats Score 52.9 to 24.0, ranking #8 overall.

In the 1 individual benchmarks reported for both models, DeepSeek-V4-Pro-0813 wins 1; 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 52.9 and ranks #8 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

Choose IBM Granite 4.2 30B

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

At a glance

The differences that matter most.

Core performance indexes
52.9
#8
24.0
#157
50.3
#12
21.8
#166
43.0
#7
9.6
#159
39.0
#8
7.9
#125
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
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
IBM Granite 4.2 30B
39.9#16
25.5#103
33.3#6
10.6#117
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

12 reported for DeepSeek-V4-Pro-0813 · 18 for IBM Granite 4.2 30B

1 shared

DeepSeek-V4-Pro-0813 outperforms in 1 benchmarks (Terminal-Bench 2.1), while IBM Granite 4.2 30B is better at 0 benchmarks.

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

Wed Sep 02 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

1570.0B diff

DeepSeek-V4-Pro-0813 has 1570.0B more parameters than IBM Granite 4.2 30B, making it 5233.3% larger.

DeepSeek
DeepSeek-V4-Pro-0813
1.6Tparameters
IBM
IBM Granite 4.2 30B
30.0Bparameters
1600.0B
DeepSeek-V4-Pro-0813
30.0B
IBM Granite 4.2 30B

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
IBM
IBM Granite 4.2 30B
Input- tokens
Output- tokens
Wed Sep 02 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V4-Pro-0813 is licensed under MIT, while IBM Granite 4.2 30B 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

IBM Granite 4.2 30B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Pro-0813 was released on 2026-08-13, while IBM Granite 4.2 30B was released on 2026-08-25.

IBM Granite 4.2 30B is 0 month newer than DeepSeek-V4-Pro-0813.

DeepSeek-V4-Pro-0813

Aug 13, 2026

2 weeks ago

IBM Granite 4.2 30B

Aug 25, 2026

1 weeks ago

1w 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek-V4-Pro-0813 and IBM Granite 4.2 30B side-by-side, then vote on the output you prefer.

DeepSeek-V4-Pro-0813
✓ Preferred
IBM Granite 4.2 30B
Open in Playground

FAQ

Common questions about DeepSeek-V4-Pro-0813 vs IBM Granite 4.2 30B.

Which is better, DeepSeek-V4-Pro-0813 or IBM Granite 4.2 30B?

DeepSeek-V4-Pro-0813 leads the LLM Stats Score 52.9 to 24.0. DeepSeek-V4-Pro-0813 is made by DeepSeek and IBM Granite 4.2 30B is made by IBM. 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 IBM Granite 4.2 30B 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%. IBM Granite 4.2 30B scores RULER 64k: 90.0%, AIME 2025: 89.2%, HMMT25: 89.2%, RULER 128k: 81.4%, MMLU-Pro: 77.6%.

What are the context window sizes for DeepSeek-V4-Pro-0813 and IBM Granite 4.2 30B?

DeepSeek-V4-Pro-0813 supports 1.0M tokens and IBM Granite 4.2 30B 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 IBM Granite 4.2 30B?

Key differences include LLM Stats Score (52.9 vs 24.0), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Pro-0813 and IBM Granite 4.2 30B?

DeepSeek-V4-Pro-0813 is developed by DeepSeek and IBM Granite 4.2 30B is developed by IBM.