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DeepSeek-V4.1-Flash-1017 vs GLM-5V-Turbo

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 30.0. DeepSeek-V4.1-Flash-1017 is 3.6x cheaper per token.

DeepSeek · Zhipu AI · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.2 to 30.0, ranking #15 overall.

On price, DeepSeek-V4.1-Flash-1017 is roughly 3.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4.1-Flash-1017 also accepts a larger context window (1,048,576 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-1017

  • overall performance matters — it scores 51.2 and ranks #15 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • cost matters — it's about 3.6x cheaper per token
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Oct 2026
  • you need open weights you can self-host or fine-tune

Choose GLM-5V-Turbo

  • you want predictable pricing at $1.20/M input and $4.00/M output

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
GLM-5V-Turbo
Zhipu AI
Core performance indexes
LLM Stats Score
51.2
#15
30.0
#142
Reasoning
48.8
#18
7.7
#302
Coding
39.3
#14
22.5
#98
Agents
38.7
#8
18.4
#89
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
$1.20 / M
Output price
$1.20 / M
$4.00 / M
Context window
1,048,576
200,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4.1-Flash-1017
GLM-5V-Turbo
Vision
32.3#25
21.0#82
Multimodal
35.0#14
21.7#78
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 19 for GLM-5V-Turbo

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and GLM-5V-Turbodon'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-1017 costs less

For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 4.0x cheaper than GLM-5V-Turbo ($1.20/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 3.3x cheaper than GLM-5V-Turbo ($4.00/1M tokens).

In conclusion, GLM-5V-Turbo is more expensive than DeepSeek-V4.1-Flash-1017.*

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

Lowest available price from all providers
Thu Oct 22 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
Zhipu AI
GLM-5V-Turbo
Input tokens$1.20
Output tokens$4.00
Best providerUnknown Organization
Notice missing or incorrect data?

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to GLM-5V-Turbo's 200,000 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while GLM-5V-Turbo is limited to 128,000 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
Zhipu AI
GLM-5V-Turbo
Input200,000 tokens
Output128,000 tokens
Thu Oct 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash-1017 and GLM-5V-Turbo 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

GLM-5V-Turbo

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, while GLM-5V-Turbo uses a proprietary license.

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

DeepSeek-V4.1-Flash-1017

MIT

Open weights

GLM-5V-Turbo

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while GLM-5V-Turbo was released on 2026-04-02.

DeepSeek-V4.1-Flash-1017 is 7 months newer than GLM-5V-Turbo.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

6mo newer
GLM-5V-Turbo

Apr 2, 2026

6 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

Provider Availability

DeepSeek-V4.1-Flash-1017 is available from DeepSeek. GLM-5V-Turbo is available from ZAI.

DeepSeek-V4.1-Flash-1017

deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

GLM-5V-Turbo

z logo
Unknown Organization
Input Price:Input: $1.20/1MOutput Price:Output: $4.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and GLM-5V-Turbo side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
GLM-5V-Turbo
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs GLM-5V-Turbo.

Which is better, DeepSeek-V4.1-Flash-1017 or GLM-5V-Turbo?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 30.0. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and GLM-5V-Turbo 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-5V-Turbo 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-5V-Turbo scores Design2Code: 94.8%, Flame-VLM-Code: 93.8%, V*: 89.0%, WebVoyager: 88.5%, PinchBench: 80.7%.

Is DeepSeek-V4.1-Flash-1017 cheaper than GLM-5V-Turbo?

DeepSeek-V4.1-Flash-1017 is 4.0x cheaper for input tokens. DeepSeek-V4.1-Flash-1017 costs $0.30/M input and $1.20/M output via deepseek. GLM-5V-Turbo costs $1.20/M input and $4.00/M output via z.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and GLM-5V-Turbo?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and GLM-5V-Turbo supports 200K 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-5V-Turbo?

Key differences include LLM Stats Score (51.2 vs 30.0), context window (1.0M vs 200K), input pricing ($0.30 vs $1.20/M), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and GLM-5V-Turbo?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and GLM-5V-Turbo is developed by Zhipu AI.

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