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DeepSeek-V4.1-Flash-1017 vs GLM-4.7

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 34.1. DeepSeek-V4.1-Flash-1017 is 1.4x cheaper per token.

DeepSeek · Zhipu AI · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 34.1, ranking #15 overall.

In the 1 individual benchmarks reported for both models, GLM-4.7 wins 1; this is a narrower head-to-head signal than the composite indexes.

On price, DeepSeek-V4.1-Flash-1017 is roughly 1.4x 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 51.0 and ranks #15 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • cost matters — it's about 1.4x 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

Choose GLM-4.7

  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
GLM-4.7
Zhipu AI
Core performance indexes
LLM Stats Score
51.0
#15
34.1
#112
Reasoning
48.6
#18
34.1
#108
Coding
39.1
#15
17.4
#137
Agents
38.6
#9
9.4
#145
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
$0.30 / M
$0.40 / M
Output price
$1.20 / M
$1.75 / M
Context window
1,048,576
202,752

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4.1-Flash-1017
GLM-4.7
Math
31.8#67
34.6#49
Tool use
30.9#7
8.3#156
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 13 for GLM-4.7

1 shared

DeepSeek-V4.1-Flash-1017 outperforms in 0 benchmarks, while GLM-4.7 is better at 1 benchmark (Humanity's Last Exam).

GLM-4.7 significantly outperforms across most benchmarks.

Mon Oct 19 2026 • llm-stats.com

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 1.3x cheaper than GLM-4.7 ($0.40/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 1.5x cheaper than GLM-4.7 ($1.75/1M tokens).

In conclusion, GLM-4.7 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
Mon Oct 19 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
Zhipu AI
GLM-4.7
Input tokens$0.40
Output tokens$1.75
Best providerDeepinfra
Notice missing or incorrect data?

Model Size

Parameter count comparison

405.2B diff

DeepSeek-V4.1-Flash-1017 has 405.2B more parameters than GLM-4.7, making it 113.2% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Zhipu AI
GLM-4.7
358.0Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
358.0B
GLM-4.7

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to GLM-4.7's 202,752 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while GLM-4.7 is limited to 202,752 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
Zhipu AI
GLM-4.7
Input202,752 tokens
Output202,752 tokens
Mon Oct 19 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash-1017 and GLM-4.7 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-4.7

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-4.7

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while GLM-4.7 was released on 2025-12-22.

DeepSeek-V4.1-Flash-1017 is 10 months newer than GLM-4.7.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

9mo newer
GLM-4.7

Dec 22, 2025

10 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-4.7 is available from DeepInfra, Fireworks, Novita.

DeepSeek-V4.1-Flash-1017

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

GLM-4.7

deepinfra logo
Deepinfra
Input Price:Input: $0.40/1MOutput Price:Output: $1.75/1M
fireworks logo
Fireworks
Input Price:Input: $0.60/1MOutput Price:Output: $2.20/1M
novita logo
Novita
Input Price:Input: $0.60/1MOutput Price:Output: $2.20/1M
* 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-4.7 side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
GLM-4.7
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs GLM-4.7.

Which is better, DeepSeek-V4.1-Flash-1017 or GLM-4.7?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 34.1. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and GLM-4.7 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-4.7 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-4.7 scores AIME 2025: 95.7%, Tau-bench: 87.4%, GPQA: 85.7%, LiveCodeBench v6: 84.9%, MMLU-Pro: 84.3%.

Is DeepSeek-V4.1-Flash-1017 cheaper than GLM-4.7?

DeepSeek-V4.1-Flash-1017 is 1.3x cheaper for input tokens. DeepSeek-V4.1-Flash-1017 costs $0.30/M input and $1.20/M output via deepseek. GLM-4.7 costs $0.40/M input and $1.75/M output via deepinfra.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and GLM-4.7?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and GLM-4.7 supports 203K 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-4.7?

Key differences include LLM Stats Score (51.0 vs 34.1), context window (1.0M vs 203K), input pricing ($0.30 vs $0.40/M). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and GLM-4.7?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and GLM-4.7 is developed by Zhipu AI.

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