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DeepSeek-R1 vs IBM Granite 4.0 Tiny Preview

Comparing DeepSeek-R1 and IBM Granite 4.0 Tiny Preview across benchmarks, pricing, and capabilities.

DeepSeek · IBM · Updated for 2026

Which is better?

DeepSeek-R1 and IBM Granite 4.0 Tiny Preview 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 4.0 Tiny Preview

  • you want the most recent training data — it shipped May 2025

At a glance

The differences that matter most.

DeepSeek-R1
DeepSeek
IBM Granite 4.0 Tiny Preview
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 · 12 for IBM Granite 4.0 Tiny Preview

No common benchmarks found

DeepSeek-R1 and IBM Granite 4.0 Tiny Previewdon'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

664.0B diff

DeepSeek-R1 has 664.0B more parameters than IBM Granite 4.0 Tiny Preview, making it 9485.7% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
IBM
IBM Granite 4.0 Tiny Preview
7.0Bparameters
671.0B
DeepSeek-R1
7.0B
IBM Granite 4.0 Tiny Preview

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 4.0 Tiny Preview
Input- tokens
Output- tokens
Mon Oct 12 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1 is licensed under MIT, while IBM Granite 4.0 Tiny Preview 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 4.0 Tiny Preview

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while IBM Granite 4.0 Tiny Preview was released on 2025-05-02.

IBM Granite 4.0 Tiny Preview is 3 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.7 years ago

IBM Granite 4.0 Tiny Preview

May 2, 2025

1.4 years ago

3mo 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?

Judge for yourself.

Run your own prompts against DeepSeek-R1 and IBM Granite 4.0 Tiny Preview side-by-side, then vote on the output you prefer.

DeepSeek-R1
✓ Preferred
IBM Granite 4.0 Tiny Preview
Open in Playground

FAQ

Common questions about DeepSeek-R1 vs IBM Granite 4.0 Tiny Preview.

Which is better, DeepSeek-R1 or IBM Granite 4.0 Tiny Preview?

DeepSeek-R1 (DeepSeek) and IBM Granite 4.0 Tiny Preview (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 4.0 Tiny Preview in benchmarks?

IBM Granite 4.0 Tiny Preview scores AttaQ: 86.1%, HumanEval: 82.4%, HumanEval+: 78.3%, GSM8k: 70.1%, IFEval: 63.0%.

What are the context window sizes for DeepSeek-R1 and IBM Granite 4.0 Tiny Preview?

DeepSeek-R1 supports 131K tokens and IBM Granite 4.0 Tiny Preview 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 4.0 Tiny Preview?

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 4.0 Tiny Preview?

DeepSeek-R1 is developed by DeepSeek and IBM Granite 4.0 Tiny Preview is developed by IBM.

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