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DeepSeek-V4.1-Flash-1017 vs GLM-4.5-Air

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 24.0.

DeepSeek · Zhipu AI · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 24.0, ranking #15 overall.

In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash-1017 wins 1; 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 51.0 and ranks #15 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Oct 2026

Choose GLM-4.5-Air

  • you are already invested in the Zhipu AI ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
GLM-4.5-Air
Zhipu AI
Core performance indexes
LLM Stats Score
51.0
#15
24.0
#187
Reasoning
48.6
#18
23.5
#185
Coding
39.1
#15
10.9
#181
Agents
38.6
#9
5.8
#164
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
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
GLM-4.5-Air
Math
31.8#67
22.1#150
Tool use
30.9#7
20.1#68
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 14 for GLM-4.5-Air

1 shared

DeepSeek-V4.1-Flash-1017 outperforms in 1 benchmarks (Humanity's Last Exam), while GLM-4.5-Air is better at 0 benchmarks.

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

Mon Oct 19 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

657.2B diff

DeepSeek-V4.1-Flash-1017 has 657.2B more parameters than GLM-4.5-Air, making it 620.0% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Zhipu AI
GLM-4.5-Air
106.0Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
106.0B
GLM-4.5-Air

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
Zhipu AI
GLM-4.5-Air
Input- tokens
Output- tokens
Mon Oct 19 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas GLM-4.5-Air 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

GLM-4.5-Air

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek-V4.1-Flash-1017

MIT

Open weights

GLM-4.5-Air

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while GLM-4.5-Air was released on 2025-07-28.

DeepSeek-V4.1-Flash-1017 is 15 months newer than GLM-4.5-Air.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

0 days ago

1.2yr newer
GLM-4.5-Air

Jul 28, 2025

1.2 years 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 GLM-4.5-Air side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
GLM-4.5-Air
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs GLM-4.5-Air.

Which is better, DeepSeek-V4.1-Flash-1017 or GLM-4.5-Air?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 24.0. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and GLM-4.5-Air is made by Zhipu AI. 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 GLM-4.5-Air 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%. GLM-4.5-Air scores MATH-500: 98.1%, AIME 2024: 89.4%, MMLU-Pro: 81.4%, TAU-bench Retail: 77.9%, BFCL-v3: 76.4%.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and GLM-4.5-Air?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and GLM-4.5-Air 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 GLM-4.5-Air?

Key differences include LLM Stats Score (51.0 vs 24.0), multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and GLM-4.5-Air?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and GLM-4.5-Air is developed by Zhipu AI.

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