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DeepSeek-V4.1-Flash vs Granite 3.3 8B Instruct

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 2.4. DeepSeek-V4.1-Flash is 1.5x cheaper per token.

DeepSeek · IBM · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 2.4, ranking #12 overall.

On price, DeepSeek-V4.1-Flash is roughly 1.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4.1-Flash also accepts a larger context window (1,040,000 input tokens), making it the stronger choice for long documents and large codebases.

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

Choose DeepSeek-V4.1-Flash

  • overall performance matters — it scores 51.8 and ranks #12 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • cost matters — it's about 1.5x cheaper per token
  • you process long inputs — it offers a 1,040,000 token context window
  • you want the most recent training data — it shipped Sep 2026

Choose Granite 3.3 8B Instruct

  • you want predictable pricing at $0.50/M input and $0.50/M output

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
Granite 3.3 8B Instruct
IBM
Core performance indexes
LLM Stats Score
51.8
#12
2.4
#314
Reasoning
48.9
#17
2.8
#303
Coding
44.4
#5
11.2
#158
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.22 / M
$0.50 / M
Output price
$0.66 / M
$0.50 / M
Context window
1,040,000
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash
Granite 3.3 8B Instruct
Math
35.2#43
2.7#289
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 14 for Granite 3.3 8B Instruct

No common benchmarks found

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

Pricing Analysis

Price comparison per million tokens

DeepSeek-V4.1-Flash costs less

For input processing, DeepSeek-V4.1-Flash ($0.22/1M tokens) is 2.3x cheaper than Granite 3.3 8B Instruct ($0.50/1M tokens).

For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 1.3x more expensive than Granite 3.3 8B Instruct ($0.50/1M tokens).

In conclusion, Granite 3.3 8B Instruct is more expensive than DeepSeek-V4.1-Flash.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat Sep 12 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash
Input tokens$0.22
Output tokens$0.66
Best providerFireworks
IBM
Granite 3.3 8B Instruct
Input tokens$0.50
Output tokens$0.50
Best providerReplicate
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

755.2B diff

DeepSeek-V4.1-Flash has 755.2B more parameters than Granite 3.3 8B Instruct, making it 9440.1% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
IBM
Granite 3.3 8B Instruct
8.0Bparameters
763.2B
DeepSeek-V4.1-Flash
8.0B
Granite 3.3 8B Instruct

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to Granite 3.3 8B Instruct's 128,000 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while Granite 3.3 8B Instruct is limited to 8,192 tokens.

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
IBM
Granite 3.3 8B Instruct
Input128,000 tokens
Output8,192 tokens
Sat Sep 12 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

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

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

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

Granite 3.3 8B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, while Granite 3.3 8B Instruct uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V4.1-Flash

MIT

Open weights

Granite 3.3 8B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while Granite 3.3 8B Instruct was released on 2025-04-16.

DeepSeek-V4.1-Flash is 17 months newer than Granite 3.3 8B Instruct.

DeepSeek-V4.1-Flash

Sep 10, 2026

0 days ago

1.4yr newer
Granite 3.3 8B Instruct

Apr 16, 2025

1.4 years ago

Knowledge Cutoff

When training data ends

Granite 3.3 8B Instruct has a documented knowledge cutoff of 2024-04-01, while DeepSeek-V4.1-Flash's cutoff date is not specified.

We can confirm Granite 3.3 8B Instruct's training data extends to 2024-04-01, but cannot make a direct comparison without DeepSeek-V4.1-Flash's cutoff date.

DeepSeek-V4.1-Flash

—

Granite 3.3 8B Instruct

Apr 2024

Provider Availability

DeepSeek-V4.1-Flash is available from Fireworks, DeepInfra, DeepSeek, Novita. Granite 3.3 8B Instruct is available from Replicate.

DeepSeek-V4.1-Flash

fireworks logo
Fireworks
Input Price:Input: $0.22/1MOutput Price:Output: $0.66/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Granite 3.3 8B Instruct

replicate logo
Replicate
Input Price:Input: $0.50/1MOutput Price:Output: $0.50/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

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

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

FAQ

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

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

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 2.4. DeepSeek-V4.1-Flash is made by DeepSeek and Granite 3.3 8B Instruct 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 compare to Granite 3.3 8B Instruct in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. Granite 3.3 8B Instruct scores HumanEval: 89.7%, AttaQ: 88.5%, HumanEval+: 86.1%, AIME 2024: 81.2%, GSM8k: 80.9%.

Is DeepSeek-V4.1-Flash cheaper than Granite 3.3 8B Instruct?

DeepSeek-V4.1-Flash is 2.3x cheaper for input tokens. DeepSeek-V4.1-Flash costs $0.22/M input and $0.66/M output via fireworks. Granite 3.3 8B Instruct costs $0.50/M input and $0.50/M output via replicate.

What are the context window sizes for DeepSeek-V4.1-Flash and Granite 3.3 8B Instruct?

DeepSeek-V4.1-Flash supports 1.0M tokens and Granite 3.3 8B Instruct supports 128K 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 and Granite 3.3 8B Instruct?

Key differences include LLM Stats Score (51.8 vs 2.4), context window (1.0M vs 128K), input pricing ($0.22 vs $0.50/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

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

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

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