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DeepSeek-V4.1-Flash-1017 vs Granite 3.3 8B Base

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to -0.8.

DeepSeek · IBM · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to -0.8, ranking #15 overall.

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

Choose DeepSeek-V4.1-Flash-1017

  • overall performance matters — it scores 51.0 and ranks #15 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Oct 2026

Choose Granite 3.3 8B Base

  • you are already invested in the IBM ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
Granite 3.3 8B Base
IBM
Core performance indexes
LLM Stats Score
51.0
#15
-0.8
#353
Reasoning
48.6
#18
-1.0
#347
Coding
39.1
#15
11.0
#180
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
— / M
Output price
$1.20 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash-1017
Granite 3.3 8B Base
Math
31.8#67
-0.8#311
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 20 for Granite 3.3 8B Base

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and Granite 3.3 8B Basedon'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

755.0B diff

DeepSeek-V4.1-Flash-1017 has 755.0B more parameters than Granite 3.3 8B Base, making it 9241.6% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
IBM
Granite 3.3 8B Base
8.2Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
8.2B
Granite 3.3 8B Base

Context Window

Maximum input and output token capacity

Only DeepSeek-V4.1-Flash-1017 specifies input context (1,048,576 tokens). Only DeepSeek-V4.1-Flash-1017 specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
IBM
Granite 3.3 8B Base
Input- tokens
Output- tokens
Mon Oct 19 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash-1017 and Granite 3.3 8B Base support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

Granite 3.3 8B Base

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, 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-V4.1-Flash-1017

MIT

Open weights

Granite 3.3 8B Base

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while Granite 3.3 8B Base was released on 2025-04-16.

DeepSeek-V4.1-Flash-1017 is 18 months newer than Granite 3.3 8B Base.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

1.5yr newer
Granite 3.3 8B Base

Apr 16, 2025

1.5 years ago

Knowledge Cutoff

When training data ends

Granite 3.3 8B Base has a documented knowledge cutoff of 2024-04-01, while DeepSeek-V4.1-Flash-1017'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-V4.1-Flash-1017's cutoff date.

DeepSeek-V4.1-Flash-1017

—

Granite 3.3 8B Base

Apr 2024

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and Granite 3.3 8B Base side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
Granite 3.3 8B Base
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs Granite 3.3 8B Base.

Which is better, DeepSeek-V4.1-Flash-1017 or Granite 3.3 8B Base?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to -0.8. DeepSeek-V4.1-Flash-1017 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-V4.1-Flash-1017 compare to Granite 3.3 8B Base in benchmarks?

DeepSeek-V4.1-Flash-1017 scores BabyVision: 92.5%, Chartography: 83.0%, DeepSWE 1.1: 77.0%, NL2Repo: 68.2%, AutomationBench: 60.5%. 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-V4.1-Flash-1017 and Granite 3.3 8B Base?

DeepSeek-V4.1-Flash-1017 supports 1.0M 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-V4.1-Flash-1017 and Granite 3.3 8B Base?

Key differences include LLM Stats Score (51.0 vs -0.8), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and Granite 3.3 8B Base?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and Granite 3.3 8B Base is developed by IBM.

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