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AI model comparison

DeepSeek V4.1 Flash vs GLM 5.3

Compare pricing, context limits, supported inputs and deployment options to choose a model for your workflow.

GLM 5.3 is a text-focused open-weight release for coding and agents. DeepSeek V4.1 Flash adds native image understanding and has a current managed Flash route. The input requirements can settle the shortlist before benchmark scores do.

Text-only and visual tasks

Use GLM’s documented text interface for repository and document tasks. For screenshots or diagrams, DeepSeek’s visual interface is relevant. Do not infer vision support from a shared model family or an agent wrapper that transcribes the image through another model.

Reasoning and templates

GLM 5.3 has explicit effort and chat-template controls. Preserve these with the checkpoint revision. For DeepSeek, record the current deepseek-flash route and account settings. Different tool parsers and retry policies can produce different agent results even with the same user prompt.

Licence and cost

GLM 5.3 has its own named licence; V4.1 Flash weights use MIT. Read the terms of the selected checkpoint and hosted service. Compare local deployment costs or the actual managed schedules instead of assigning an unverified rate to a download.

Side-by-sideCapabilities and practical differences

DeepSeek

DeepSeek V4.1 Flash

DeepSeek V4.1 Flash is a multimodal mixture-of-experts model released, with native image understanding.

Context
1.05M
Max output
393.22K
Input / 1M tokens
From $0.15
Output / 1M tokens
From $0.60

Pricing conditions: Off-peak USD rates per million tokens are $0.15 uncached input, $0.003 cached input and $0.60 output. Peak rates are twice those amounts, during 01:00–04:00 and 06:00–10:00 UTC on weekdays excluding Chinese public holidays. The current model ID is deepseek-flash.

Accepts

  • Text input
  • Image input

Produces

  • Text output
Full model profileapi-docs.deepseek.com ↗
VS

Z.ai / Zhipu AI

GLM 5.3

GLM 5.3 is Z.ai's open-weight text model for coding and extended agent tasks, built on the same base model as GLM 5.2.

Context
1M
Max output
128K

Accepts

  • Text input

Produces

  • Text output
Full model profiledocs.z.ai ↗

At a glance

Key differences

Compare the available figures below, then try both models on the work you need to do.

DeepSeek V4.1 Flash

  • Context capacity: 1.05M
  • Maximum output: 393.22K

Context capacity

Higher listed limit

DeepSeek V4.1 Flash:1.05M

GLM 5.3:1M

DeepSeek V4.1 Flash

Maximum output

Higher listed limit

DeepSeek V4.1 Flash:393.22K

GLM 5.3:128K

DeepSeek V4.1 Flash

Specifications

Pricing, limits and capabilities

Specifications for DeepSeek V4.1 Flash and GLM 5.3. Higher limits and lower prices describe these figures only.
SpecificationDeepSeek V4.1 FlashGLM 5.3
ProviderDeepSeekZ.ai / Zhipu AI
Listed pricing routeDeepSeekZ.ai / Zhipu AI
Model family——
Accepted inputstext, imagetext
Produced outputstexttext
Context window1.05MHigher1M
Max output393.22KHigher128K
Input price / 1MFrom $0.15—
Output price / 1MFrom $0.60—
Reasoning modeDocumentedDocumented
Tool callingNot documentedDocumented
Image inputDocumentedNot documented
Audio inputNot documentedNot documented
Structured outputNot documentedDocumented
LicenseMITGLM-5.3 licence

Workload guidance

Which model should you choose?

Run a shared coding set

Give both agents ordinary and difficult issues with executable tests. Include an error recovery task and a requirement that should trigger a request for missing information. Count regressions, repeated ineffective actions and review time.

Keep visual tasks in their own results rather than averaging them into a text-only comparison. Choose from accepted patches and deployment constraints. Publisher scores are useful evidence for designing the evaluation, but this guide does not declare an independent winner.

Source notes

This is a documentation-based selection guide, not an independent benchmark. Publisher source 1 · Publisher source 2 · Publisher source 3.

Documentation and model profiles

Explore each model’s features, API requirements and licence terms in the sources below.

Questions people ask

It brings together documented inputs and outputs, token limits, deployment terms and available pricing. When both models have source-linked, verified results on a shared benchmark, those results are shown with their individual sources. The comparison is a starting point for evaluating your own workload.

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