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DeepSeek-V3 0324 vs IBM Granite 4.2 30B

IBM Granite 4.2 30B leads the LLM Stats Score 24.0 to 13.7.

DeepSeek · IBM · Updated for 2026

Which is better?

IBM Granite 4.2 30B leads the overall LLM Stats Score 24.0 to 13.7, ranking #156 overall.

In the 2 individual benchmarks reported for both models, DeepSeek-V3 0324 wins 2; 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-V3 0324

  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results

Choose IBM Granite 4.2 30B

  • overall performance matters — it scores 24.0 and ranks #156 on LLM Stats
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Core performance indexes
13.7
#229
24.0
#156
13.9
#219
21.8
#165
4.1
#200
9.6
#159
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
Input price
$0.28 / M
— / M
Output price
$1.14 / M
— / M
Context window
163,840

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V3 0324
IBM Granite 4.2 30B
16.1#200
25.6#103
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

5 reported for DeepSeek-V3 0324 · 18 for IBM Granite 4.2 30B

2 shared

DeepSeek-V3 0324 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while IBM Granite 4.2 30B is better at 0 benchmarks.

DeepSeek-V3 0324 significantly outperforms across most benchmarks.

Mon Aug 31 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

641.0B diff

DeepSeek-V3 0324 has 641.0B more parameters than IBM Granite 4.2 30B, making it 2136.7% larger.

DeepSeek
DeepSeek-V3 0324
671.0Bparameters
IBM
IBM Granite 4.2 30B
30.0Bparameters
671.0B
DeepSeek-V3 0324
30.0B
IBM Granite 4.2 30B

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 0324 specifies input context (163,840 tokens). Only DeepSeek-V3 0324 specifies output context (163,840 tokens).

DeepSeek
DeepSeek-V3 0324
Input163,840 tokens
Output163,840 tokens
IBM
IBM Granite 4.2 30B
Input- tokens
Output- tokens
Mon Aug 31 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), 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-V3 0324

MIT + Model License (Commercial use allowed)

Open weights

IBM Granite 4.2 30B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 0324 was released on 2025-03-25, while IBM Granite 4.2 30B was released on 2026-08-25.

IBM Granite 4.2 30B is 17 months newer than DeepSeek-V3 0324.

DeepSeek-V3 0324

Mar 25, 2025

1.4 years ago

IBM Granite 4.2 30B

Aug 25, 2026

5 days ago

1.4yr 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-V3 0324 and IBM Granite 4.2 30B side-by-side, then vote on the output you prefer.

DeepSeek-V3 0324
✓ Preferred
IBM Granite 4.2 30B
Open in Playground

FAQ

Common questions about DeepSeek-V3 0324 vs IBM Granite 4.2 30B.

Which is better, DeepSeek-V3 0324 or IBM Granite 4.2 30B?

IBM Granite 4.2 30B leads the LLM Stats Score 24.0 to 13.7. DeepSeek-V3 0324 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-V3 0324 compare to IBM Granite 4.2 30B in benchmarks?

DeepSeek-V3 0324 scores MATH-500: 94.0%, MMLU-Pro: 81.2%, GPQA: 68.4%, AIME 2024: 59.4%, LiveCodeBench: 49.2%. 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-V3 0324 and IBM Granite 4.2 30B?

DeepSeek-V3 0324 supports 164K 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-V3 0324 and IBM Granite 4.2 30B?

Key differences include LLM Stats Score (13.7 vs 24.0), licensing (MIT + Model License (Commercial use allowed) vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 0324 and IBM Granite 4.2 30B?

DeepSeek-V3 0324 is developed by DeepSeek and IBM Granite 4.2 30B is developed by IBM.