DeepSeek-V4.1-Flash-1017 vs GLM-4.5V
Comparing DeepSeek-V4.1-Flash-1017 and GLM-4.5V across benchmarks, pricing, and capabilities.
DeepSeek · Zhipu AI · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash-1017 and GLM-4.5V trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek-V4.1-Flash-1017 is roughly 1.8x 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
- cost matters — it's about 1.8x 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-4.5V
- you want predictable pricing at $0.55/M input and $2.19/M output
At a glance
The differences that matter most.
Individual benchmarks
11 reported for DeepSeek-V4.1-Flash-1017 · 0 for GLM-4.5V
DeepSeek-V4.1-Flash-1017 and GLM-4.5Vdon'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
For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 1.8x cheaper than GLM-4.5V ($0.55/1M tokens).
For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 1.8x cheaper than GLM-4.5V ($2.19/1M tokens).
In conclusion, GLM-4.5V is more expensive than DeepSeek-V4.1-Flash-1017.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4.1-Flash-1017 has 655.2B more parameters than GLM-4.5V, making it 606.7% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to GLM-4.5V's 131,072 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while GLM-4.5V is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both DeepSeek-V4.1-Flash-1017 and GLM-4.5V support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4.1-Flash-1017
GLM-4.5V
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while GLM-4.5V was released on 2025-08-11.
DeepSeek-V4.1-Flash-1017 is 14 months newer than GLM-4.5V.
Oct 17, 2026
2 days ago
1.2yr newerAug 11, 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.
Provider Availability
DeepSeek-V4.1-Flash-1017 is available from DeepSeek. GLM-4.5V is available from Fireworks, Novita.
DeepSeek-V4.1-Flash-1017
GLM-4.5V
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash-1017 and GLM-4.5V side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash-1017 vs GLM-4.5V.
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