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DeepSeek-R1 vs IBM Granite 4.2 30B

Comparing DeepSeek-R1 and IBM Granite 4.2 30B across benchmarks, pricing, and capabilities.

DeepSeek · IBM · Updated for 2026

Which is better?

DeepSeek-R1 and IBM Granite 4.2 30B trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-R1

  • you want predictable pricing at $0.55/M input and $2.19/M output

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.

DeepSeek-R1
DeepSeek
IBM Granite 4.2 30B
IBM
Benchmark wins
—
—
Input price
$0.55 / M
— / M
Output price
$2.19 / M
— / M
Context window
131,072
—

Individual benchmarks

0 reported for DeepSeek-R1 · 18 for IBM Granite 4.2 30B

No common benchmarks found

DeepSeek-R1 and IBM Granite 4.2 30Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

641.0B diff

DeepSeek-R1 has 641.0B more parameters than IBM Granite 4.2 30B, making it 2136.7% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
IBM
IBM Granite 4.2 30B
30.0Bparameters
671.0B
DeepSeek-R1
30.0B
IBM Granite 4.2 30B

Context Window

Maximum input and output token capacity

Only DeepSeek-R1 specifies input context (131,072 tokens). Only DeepSeek-R1 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1
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-R1 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-R1

MIT

Open weights

IBM Granite 4.2 30B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while IBM Granite 4.2 30B was released on 2026-08-25.

IBM Granite 4.2 30B is 19 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.6 years ago

IBM Granite 4.2 30B

Aug 25, 2026

6 days ago

1.6yr 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-R1 and IBM Granite 4.2 30B side-by-side, then vote on the output you prefer.

DeepSeek-R1
✓ Preferred
IBM Granite 4.2 30B
Open in Playground

FAQ

Common questions about DeepSeek-R1 vs IBM Granite 4.2 30B.

Which is better, DeepSeek-R1 or IBM Granite 4.2 30B?

DeepSeek-R1 (DeepSeek) and IBM Granite 4.2 30B (IBM) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-R1 compare to IBM Granite 4.2 30B in benchmarks?

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-R1 and IBM Granite 4.2 30B?

DeepSeek-R1 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-R1 and IBM Granite 4.2 30B?

Key differences include licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-R1 and IBM Granite 4.2 30B?

DeepSeek-R1 is developed by DeepSeek and IBM Granite 4.2 30B is developed by IBM.

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