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DeepSeek-V4.1-Flash-1017 vs K2 Horizon 375B-A23B

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 50.7 to 38.5.

DeepSeek · Institute of Foundation Models · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 50.7 to 38.5, ranking #17 overall.

In the 2 individual benchmarks reported for both models, DeepSeek-V4.1-Flash-1017 wins 2; 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-V4.1-Flash-1017

  • overall performance matters — it scores 50.7 and ranks #17 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you want the most recent training data — it shipped Oct 2026

Choose K2 Horizon 375B-A23B

  • you are already invested in the Institute of Foundation Models ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
K2 Horizon 375B-A23B
Institute of Foundation Models
Core performance indexes
LLM Stats Score
50.7
#17
38.5
#83
Reasoning
48.0
#22
37.3
#87
Coding
40.0
#15
21.2
#114
Agents
39.0
#11
23.9
#74
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
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

2 shared
Index
DeepSeek-V4.1-Flash-1017
K2 Horizon 375B-A23B
Math
31.8#70
29.7#89
Tool use
31.4#8
22.3#62
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 18 for K2 Horizon 375B-A23B

2 shared

DeepSeek-V4.1-Flash-1017 outperforms in 2 benchmarks (AutomationBench, Humanity's Last Exam), while K2 Horizon 375B-A23B is better at 0 benchmarks.

DeepSeek-V4.1-Flash-1017 significantly outperforms across most benchmarks.

Fri Oct 30 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

388.2B diff

DeepSeek-V4.1-Flash-1017 has 388.2B more parameters than K2 Horizon 375B-A23B, making it 103.5% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Institute of Foundation Models
K2 Horizon 375B-A23B
375.0Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
375.0B
K2 Horizon 375B-A23B

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
Institute of Foundation Models
K2 Horizon 375B-A23B
Input- tokens
Output- tokens
Fri Oct 30 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas K2 Horizon 375B-A23B does not.

DeepSeek-V4.1-Flash-1017 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

K2 Horizon 375B-A23B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, while K2 Horizon 375B-A23B 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

K2 Horizon 375B-A23B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while K2 Horizon 375B-A23B was released on 2026-09-03.

DeepSeek-V4.1-Flash-1017 is 1 month newer than K2 Horizon 375B-A23B.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

1 weeks ago

1mo newer
K2 Horizon 375B-A23B

Sep 3, 2026

1 months ago

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-V4.1-Flash-1017 and K2 Horizon 375B-A23B side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
K2 Horizon 375B-A23B
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs K2 Horizon 375B-A23B.

Which is better, DeepSeek-V4.1-Flash-1017 or K2 Horizon 375B-A23B?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 50.7 to 38.5. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and K2 Horizon 375B-A23B is made by Institute of Foundation Models. 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 K2 Horizon 375B-A23B 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%. K2 Horizon 375B-A23B scores GPQA: 87.3%, AA-LCR: 76.0%, OmniScience (non-hallucination rate): 74.7%, BrowseComp: 72.8%, Terminal-Bench 2.1: 70.2%.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and K2 Horizon 375B-A23B?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and K2 Horizon 375B-A23B 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 K2 Horizon 375B-A23B?

Key differences include LLM Stats Score (50.7 vs 38.5), multimodal support (yes vs no), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and K2 Horizon 375B-A23B?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and K2 Horizon 375B-A23B is developed by Institute of Foundation Models.

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