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DeepSeek-V4.1-Flash vs ERNIE 5.0

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 33.4.

DeepSeek · Baidu · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 33.4, ranking #12 overall.

The models split the 2 individual benchmarks reported for both models evenly.

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 — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026
  • you need open weights you can self-host or fine-tune

Choose ERNIE 5.0

  • you are already invested in the Baidu ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
ERNIE 5.0
Baidu
Core performance indexes
LLM Stats Score
51.8
#12
33.4
#98
Reasoning
48.9
#17
33.0
#98
Cost, coverage & limits
Benchmark wins
1 of 2
1 of 2
Input price
$0.22 / M
— / M
Output price
$0.66 / M
— / M
Context window
1,040,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash
ERNIE 5.0
Math
35.2#43
31.0#71
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 5 for ERNIE 5.0

2 shared

DeepSeek-V4.1-Flash outperforms in 1 benchmarks (GPQA), while ERNIE 5.0 is better at 1 benchmark (Humanity's Last Exam).

Both models are evenly matched across the benchmarks.

Fri Sep 11 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only DeepSeek-V4.1-Flash specifies input context (1,040,000 tokens). Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Baidu
ERNIE 5.0
Input- tokens
Output- tokens
Fri Sep 11 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash and ERNIE 5.0 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

ERNIE 5.0

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, while ERNIE 5.0 uses a proprietary license.

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

DeepSeek-V4.1-Flash

MIT

Open weights

ERNIE 5.0

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while ERNIE 5.0 was released on 2026-01-22.

DeepSeek-V4.1-Flash is 8 months newer than ERNIE 5.0.

DeepSeek-V4.1-Flash

Sep 10, 2026

0 days ago

7mo newer
ERNIE 5.0

Jan 22, 2026

7 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?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash and ERNIE 5.0 side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
ERNIE 5.0
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs ERNIE 5.0.

Which is better, DeepSeek-V4.1-Flash or ERNIE 5.0?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 33.4. DeepSeek-V4.1-Flash is made by DeepSeek and ERNIE 5.0 is made by Baidu. 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 ERNIE 5.0 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%. ERNIE 5.0 scores AIME 2025: 87.0%, MMLU-Pro: 87.0%, GPQA: 85.0%, SimpleQA: 75.0%, Humanity's Last Exam: 39.0%.

What are the context window sizes for DeepSeek-V4.1-Flash and ERNIE 5.0?

DeepSeek-V4.1-Flash supports 1.0M tokens and ERNIE 5.0 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 and ERNIE 5.0?

Key differences include LLM Stats Score (51.8 vs 33.4), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and ERNIE 5.0?

DeepSeek-V4.1-Flash is developed by DeepSeek and ERNIE 5.0 is developed by Baidu.

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