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DeepSeek-V3.2 (Thinking) vs IBM Granite 4.2 3B

DeepSeek-V3.2 (Thinking) leads the LLM Stats Score 33.0 to 15.6.

DeepSeek · IBM · Updated for 2026

Which is better?

DeepSeek-V3.2 (Thinking) leads the overall LLM Stats Score 33.0 to 15.6, ranking #90 overall.

In the 3 individual benchmarks reported for both models, DeepSeek-V3.2 (Thinking) 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-V3.2 (Thinking)

  • overall performance matters — it scores 33.0 and ranks #90 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 3 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.

Core performance indexes
33.0
#90
15.6
#213
33.0
#90
12.0
#234
22.9
#69
-6.7
#247
11.1
#97
2.0
#152
Cost, coverage & limits
Benchmark wins
3 of 3
0 of 3
Input price
$0.28 / M
— / M
Output price
$0.42 / M
— / M
Context window
131,072

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V3.2 (Thinking)
IBM Granite 4.2 3B
30.6#70
13.7#216
9.4#124
5.3#144
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for DeepSeek-V3.2 (Thinking) · 13 for IBM Granite 4.2 3B

3 shared

DeepSeek-V3.2 (Thinking) outperforms in 3 benchmarks (AIME 2025, GPQA, MMLU-Pro), while IBM Granite 4.2 3B is better at 0 benchmarks.

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks.

Tue Sep 01 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

682.0B diff

DeepSeek-V3.2 (Thinking) has 682.0B more parameters than IBM Granite 4.2 3B, making it 22733.3% larger.

DeepSeek
DeepSeek-V3.2 (Thinking)
685.0Bparameters
IBM
IBM Granite 4.2 3B
3.0Bparameters
685.0B
DeepSeek-V3.2 (Thinking)
3.0B
IBM Granite 4.2 3B

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2 (Thinking) specifies input context (131,072 tokens). Only DeepSeek-V3.2 (Thinking) specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
IBM
IBM Granite 4.2 3B
Input- tokens
Output- tokens
Tue Sep 01 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2 (Thinking) is licensed under MIT, 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-V3.2 (Thinking)

MIT

Open weights

IBM Granite 4.2 3B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while IBM Granite 4.2 3B was released on 2026-08-25.

IBM Granite 4.2 3B is 9 months newer than DeepSeek-V3.2 (Thinking).

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

9 months ago

IBM Granite 4.2 3B

Aug 25, 2026

6 days ago

8mo 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-V3.2 (Thinking) and IBM Granite 4.2 3B side-by-side, then vote on the output you prefer.

DeepSeek-V3.2 (Thinking)
✓ Preferred
IBM Granite 4.2 3B
Open in Playground

FAQ

Common questions about DeepSeek-V3.2 (Thinking) vs IBM Granite 4.2 3B.

Which is better, DeepSeek-V3.2 (Thinking) or IBM Granite 4.2 3B?

DeepSeek-V3.2 (Thinking) leads the LLM Stats Score 33.0 to 15.6. DeepSeek-V3.2 (Thinking) 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-V3.2 (Thinking) compare to IBM Granite 4.2 3B in benchmarks?

DeepSeek-V3.2 (Thinking) scores AIME 2025: 93.1%, HMMT 2025: 90.2%, MMLU-Pro: 85.0%, LiveCodeBench: 83.3%, GPQA: 82.4%. 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-V3.2 (Thinking) and IBM Granite 4.2 3B?

DeepSeek-V3.2 (Thinking) 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-V3.2 (Thinking) and IBM Granite 4.2 3B?

Key differences include LLM Stats Score (33.0 vs 15.6), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2 (Thinking) and IBM Granite 4.2 3B?

DeepSeek-V3.2 (Thinking) is developed by DeepSeek and IBM Granite 4.2 3B is developed by IBM.