GLM-5.2 vs DeepSeek V4 Flash

GLM-5.2 from Z.ai and DeepSeek V4 Flash from DeepSeek are shown side by side so you can compare pricing, model IDs, context and output limits, modalities, tool use, release details, and benchmark results where data is available.

Overall Recommendation

For teams choosing between Z.ai GLM and DeepSeek, select GLM-5.2 for long-horizon software engineering and sustained agent execution. Choose DeepSeek V4 Flash for high-volume text workloads when TokenHub price and maximum output matter more: both list 1M context, but Flash is cheaper and lists 384K max output versus GLM-5.2 at 131K.

Comparison Highlights

Based On Current Page Data

GLM-5.2Z.ai

DeepSeek V4 FlashDeepSeek

How To Read It

Best For

Long-horizon codingproject-scale engineering agents

Cost-sensitivehigh-throughput long-context text generation

How To Read ItUse-case synthesis from model capabilities and positioning.

Workload Fit

1M contextFlexible reasoningSustained tool use

1M context384K outputLow TokenHub price

How To Read ItThe workloads each model is most directly shaped for.

Input

$1.1429/M

$0.4286/MEdge

How To Read ItLower is better when prompts or retrieval payloads are large.

Output

$4/M

$1.2857/MEdge

How To Read ItLower is better for reasoning-heavy or long-generation traffic.

Context length

How To Read ItHigher is better for repositories, retrieval packs, and transcripts.

Input modalities

Text

How To Read ItBroader input support reduces the need for separate vision or video models.

Model Selection Guide

GLM-5.2Z.ai

Choose GLM-5.2 When

Z.ai positions GLM-5.2 specifically for long-horizon tasks, coding, and more reliable end-to-end execution
TokenHub lists 1M context, 131K max output, reasoning, tool calling, and OpenAI, Anthropic, and Gemini endpoints
The official release supports multiple reasoning-effort levels to trade capability against latency

DeepSeek V4 FlashDeepSeek

Choose DeepSeek V4 Flash When

DeepSeek V4 Flash uses a smaller 284B/13B-active MoE designed around efficient million-token inference
TokenHub lists a 384K maximum output, nearly three times GLM-5.2’s listed 131K
Its current TokenHub input and output prices are materially lower than GLM-5.2

Basic Information

GLM-5.2Z.ai

DeepSeek V4 FlashDeepSeek

Name

GLM-5.2

Model id

glm-5.2

Data source

TokenHub production catalog

Intro

GLM-5.2 is Z.ai’s flagship foundation model for long-horizon engineering tasks. It emphasizes a usable 1M-token context window for project-scale code and system context, more stable execution on long tasks, and better adherence to engineering standards. It is positioned for full development workflows, from requirements and repository analysis to implementation, testing, and multi-platform deployment, where large context and sustained agent behavior matter.

Author

Z.ai

Released date

2026-06-13

Context length

Max output tokens

131.1K

Name

DeepSeek V4 Flash

Model id

deepseek-v4-flash

Data source

TokenHub production catalog

Intro

DeepSeek V4 Flash keeps the V4 family’s 1M-token context window but uses a lighter MoE configuration, commonly described as 284B total parameters with 13B activated parameters. The emphasis is throughput: fast inference, lower cost per call, and production workloads that still need long-context handling. It is the better fit when the task volume is high and the workload benefits from V4-style long-context architecture without always requiring the deepest reasoning tier.

Author

DeepSeek

Released date

2026-04-24

Context length

Max output tokens

384K

Name

GLM-5.2

Name

DeepSeek V4 Flash

Model id

glm-5.2

Model id

deepseek-v4-flash

Data source

TokenHub production catalog

Data source

TokenHub production catalog

Intro

Author

Z.ai

Author

DeepSeek

Released date

2026-06-13

Released date

2026-04-24

Context length

Max output tokens

131.1K

Max output tokens

384K

Pricing

GLM-5.2Z.ai

DeepSeek V4 FlashDeepSeek

Input

$1.1429/M

Output

$4/M

Cached input

$0.2857/M

Input

$0.4286/M

Output

$1.2857/M

Cached input

$0.0143/M

Input

$1.1429/M

Input

$0.4286/M

Output

$4/M

Output

$1.2857/M

Cached input

$0.2857/M

Cached input

$0.0143/M

Capabilities

GLM-5.2Z.ai

DeepSeek V4 FlashDeepSeek

Reasoning

Knowledge

n/a

Attachment

Input modalities

Text

Output modalities

Text

Temperature

Tool use

Reasoning

Knowledge

2025-05-01

Attachment

Input modalities

Text

Output modalities

Text

Temperature

Tool use

Reasoning

Knowledge

n/a

Knowledge

2025-05-01

Attachment

Input modalities

Text

Input modalities

Text

Output modalities

Text

Output modalities

Text

Temperature

Tool use

Benchmark

GLM-5.2Z.ai

DeepSeek V4 FlashDeepSeek

Intelligence

wins51.1

Coding

wins68.8

Intelligence

40.3

Coding

38.7

Knowledge & Reasoning

GPQA

wins89.5%

HLE

wins40.1%

GPQA

89.4%

HLE

32.1%

Coding

SciCode

wins50.5%

Terminal-Bench Hard

wins50.8%

SciCode

44.9%

Terminal-Bench Hard

35.6%

Instruction Following & Agent Tasks

IFBench

73.3%

AA-LCR

wins71.3%

Tau2

wins99.1%

IFBench

wins79.2%

AA-LCR

63%

Tau2

95.0%

FAQ

Which model is better, GLM-5.2 or DeepSeek V4 Flash?

Neither model is universally better. Start with the Model Selection Guide above to match each model to your task, then use pricing, context length, maximum output, and capability rows to confirm the operational fit.

Is DeepSeek V4 Flash cheaper than GLM-5.2?

Use the pricing rows above to compare input, output, and cached input prices for GLM-5.2 and DeepSeek V4 Flash.

Which model supports a longer context length?

GLM-5.2 lists 1M context length, while DeepSeek V4 Flash lists 1M.

Can I access both models through TokenHub?

If both models are available in the TokenHub catalog, you can route requests to GLM-5.2 and DeepSeek V4 Flash through the TokenHub API.