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DeepSeek-V3 vs Granite 3.3 8B Base

DeepSeek-V3 leads the LLM Stats Score 15.7 to -0.5.

DeepSeek · IBM · Updated for 2026

Which is better?

DeepSeek-V3 leads the overall LLM Stats Score 15.7 to -0.5, ranking #228 overall.

In the 5 individual benchmarks reported for both models, DeepSeek-V3 wins 4; 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

  • overall performance matters — it scores 15.7 and ranks #228 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 4 of 5 exact shared results

Choose Granite 3.3 8B Base

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

At a glance

The differences that matter most.

DeepSeek-V3
DeepSeek
Granite 3.3 8B Base
IBM
Core performance indexes
LLM Stats Score
15.7
#228
-0.5
#329
Reasoning
14.8
#227
-0.7
#323
Coding
6.2
#192
11.1
#161
Cost, coverage & limits
Benchmark wins
4 of 5
1 of 5
Input price
$0.27 / M
— / M
Output price
$0.89 / M
— / M
Context window
131,072
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
DeepSeek-V3
Granite 3.3 8B Base
Math
18.0#188
-0.8#298
Finance
19.9#82
-7.2#219
Legal
19.9#67
-6.0#201
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V3 · 20 for Granite 3.3 8B Base

5 shared

DeepSeek-V3 outperforms in 4 benchmarks (DROP, IFEval, MATH-500, MMLU), while Granite 3.3 8B Base is better at 1 benchmark (AIME 2024).

DeepSeek-V3 significantly outperforms across most benchmarks.

Mon Sep 21 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

662.8B diff

DeepSeek-V3 has 662.8B more parameters than Granite 3.3 8B Base, making it 8113.0% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
IBM
Granite 3.3 8B Base
8.2Bparameters
671.0B
DeepSeek-V3
8.2B
Granite 3.3 8B Base

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
Granite 3.3 8B Base
Input- tokens
Output- tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Granite 3.3 8B Base supports multimodal inputs, whereas DeepSeek-V3 does not.

Granite 3.3 8B Base can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3

Text
Images
Audio
Video

Granite 3.3 8B Base

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Granite 3.3 8B Base 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

Granite 3.3 8B Base

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Granite 3.3 8B Base was released on 2025-04-16.

Granite 3.3 8B Base is 4 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.7 years ago

Granite 3.3 8B Base

Apr 16, 2025

1.4 years ago

3mo newer

Knowledge Cutoff

When training data ends

Granite 3.3 8B Base has a documented knowledge cutoff of 2024-04-01, while DeepSeek-V3's cutoff date is not specified.

We can confirm Granite 3.3 8B Base's training data extends to 2024-04-01, but cannot make a direct comparison without DeepSeek-V3's cutoff date.

DeepSeek-V3

—

Granite 3.3 8B Base

Apr 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V3 and Granite 3.3 8B Base side-by-side, then vote on the output you prefer.

DeepSeek-V3
✓ Preferred
Granite 3.3 8B Base
Open in Playground

FAQ

Common questions about DeepSeek-V3 vs Granite 3.3 8B Base.

Which is better, DeepSeek-V3 or Granite 3.3 8B Base?

DeepSeek-V3 leads the LLM Stats Score 15.7 to -0.5. DeepSeek-V3 is made by DeepSeek and Granite 3.3 8B Base 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 Granite 3.3 8B Base in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Granite 3.3 8B Base scores HumanEval: 89.7%, AttaQ: 88.5%, HumanEval+: 86.1%, AIME 2024: 81.2%, HellaSwag: 80.1%.

What are the context window sizes for DeepSeek-V3 and Granite 3.3 8B Base?

DeepSeek-V3 supports 131K tokens and Granite 3.3 8B Base 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 Granite 3.3 8B Base?

Key differences include LLM Stats Score (15.7 vs -0.5), multimodal support (no vs yes), 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 Granite 3.3 8B Base?

DeepSeek-V3 is developed by DeepSeek and Granite 3.3 8B Base is developed by IBM.

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