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DeepSeek-V3 vs IBM Granite 4.2 3B

DeepSeek-V3 and IBM Granite 4.2 3B are closely matched at 15.8 and 15.6 on the LLM Stats Score.

DeepSeek · IBM · Updated for 2026

Which is better?

DeepSeek-V3 and IBM Granite 4.2 3B are closely matched on the overall LLM Stats Score at 15.8 and 15.6.

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

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

Choose IBM Granite 4.2 3B

  • 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 3B
IBM
Core performance indexes
LLM Stats Score
15.8
#211
15.6
#213
Reasoning
14.9
#213
12.0
#234
Coding
6.5
#179
-6.7
#247
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
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 3B
Math
18.2#173
13.7#216
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V3 · 13 for IBM Granite 4.2 3B

2 shared

DeepSeek-V3 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while IBM Granite 4.2 3B is better at 0 benchmarks.

DeepSeek-V3 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

668.0B diff

DeepSeek-V3 has 668.0B more parameters than IBM Granite 4.2 3B, making it 22266.7% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
IBM
IBM Granite 4.2 3B
3.0Bparameters
671.0B
DeepSeek-V3
3.0B
IBM Granite 4.2 3B

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 3B
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 3B 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 3B

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 3B was released on 2026-08-25.

IBM Granite 4.2 3B is 20 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.7 years ago

IBM Granite 4.2 3B

Aug 25, 2026

6 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 3B side-by-side, then vote on the output you prefer.

DeepSeek-V3
✓ Preferred
IBM Granite 4.2 3B
Open in Playground

FAQ

Common questions about DeepSeek-V3 vs IBM Granite 4.2 3B.

Which is better, DeepSeek-V3 or IBM Granite 4.2 3B?

DeepSeek-V3 and IBM Granite 4.2 3B are closely matched on the LLM Stats Score at 15.8 and 15.6. DeepSeek-V3 is made by DeepSeek and IBM Granite 4.2 3B 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 3B 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 3B scores AIME 2025: 78.3%, IFBench: 74.3%, LiveCodeBench v6: 69.7%, MMLU-Pro: 67.8%, RULER 64k: 67.5%.

What are the context window sizes for DeepSeek-V3 and IBM Granite 4.2 3B?

DeepSeek-V3 supports 131K tokens and IBM Granite 4.2 3B 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 3B?

Key differences include LLM Stats Score (15.8 vs 15.6), 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 3B?

DeepSeek-V3 is developed by DeepSeek and IBM Granite 4.2 3B is developed by IBM.

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