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DeepSeek-V3 vs IBM Granite 4.2 30B

IBM Granite 4.2 30B leads the LLM Stats Score 24.0 to 15.8.

DeepSeek · IBM · Updated for 2026

Which is better?

IBM Granite 4.2 30B leads the overall LLM Stats Score 24.0 to 15.8, ranking #156 overall.

In the 3 individual benchmarks reported for both models, IBM Granite 4.2 30B wins 3; 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

  • you want predictable pricing at $0.27/M input and $1.10/M output

Choose IBM Granite 4.2 30B

  • overall performance matters — it scores 24.0 and ranks #156 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 3 exact shared results
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

DeepSeek-V3
DeepSeek
IBM Granite 4.2 30B
IBM
Core performance indexes
LLM Stats Score
15.8
#211
24.0
#156
Reasoning
14.9
#213
21.8
#165
Coding
6.5
#179
9.6
#159
Cost, coverage & limits
Benchmark wins
0 of 3
3 of 3
Input price
$0.27 / M
— / M
Output price
$1.10 / M
— / M
Context window
131,072
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V3
IBM Granite 4.2 30B
Math
18.2#173
25.6#103
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

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

3 shared

DeepSeek-V3 outperforms in 0 benchmarks, while IBM Granite 4.2 30B is better at 3 benchmarks (GPQA, MMLU-Pro, SWE-Bench Verified).

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

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

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 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 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

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 was released on 2024-12-25, while IBM Granite 4.2 30B was released on 2026-08-25.

IBM Granite 4.2 30B is 20 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.7 years ago

IBM Granite 4.2 30B

Aug 25, 2026

5 days ago

1.7yr 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 and IBM Granite 4.2 30B side-by-side, then vote on the output you prefer.

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

FAQ

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

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

IBM Granite 4.2 30B leads the LLM Stats Score 24.0 to 15.8. DeepSeek-V3 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 compare to IBM Granite 4.2 30B in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. 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 and IBM Granite 4.2 30B?

DeepSeek-V3 supports 131K 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 and IBM Granite 4.2 30B?

Key differences include LLM Stats Score (15.8 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 and IBM Granite 4.2 30B?

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

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