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BenchLM
Model A
Gemini 3.5 Flash Cyber

Google

—

Evidence status unavailable

90% interval unavailable

Gemini 3.5 Flash Cyber vs GLM-5.3

Updated August 14, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B
GLM-5.3

Z.AI

—

Evidence status unavailable

90% interval unavailable

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.

1 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

No workload recommendation clears the current evidence threshold.

Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.

Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    Not enough matched evidence

    A complete context comparison is not sourced.

    Confidence: limited

  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
1
Gemini 3.5 Flash Cyber only
0
GLM-5.3 only
15
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Agentic

Not comparable
Gemini 3.5 Flash Cyber
Not measured
GLM-5.3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Gemini 3.5 Flash Cyber
Not measured
GLM-5.3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Gemini 3.5 Flash Cyber
Not measured
GLM-5.3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Gemini 3.5 Flash Cyber
Not measured
GLM-5.3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Math

Not comparable
Gemini 3.5 Flash Cyber
Not measured
GLM-5.3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.5 Flash Cyber
Not measured
GLM-5.3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 3.5 Flash Cyber
Not measured
GLM-5.3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.5 Flash Cyber
Not measured
GLM-5.3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Gemini 3.5 Flash Cyber
API rate not published
Fit state unavailable
GLM-5.3
API rate not published
Fits in one request

Gemini 3.5 Flash Cyber has no comparable published API token rate. GLM-5.3 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Gemini 3.5 Flash Cyber
API rate not published
Fit state unavailable
GLM-5.3
API rate not published
Fits in one request

Gemini 3.5 Flash Cyber has no comparable published API token rate. GLM-5.3 has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Gemini 3.5 Flash Cyber
API rate not published
Fit state unavailable
Cached-input rate unavailable
GLM-5.3
API rate not published
Fits in one request
Cached-input rate unavailable

Gemini 3.5 Flash Cyber has no comparable published API token rate. GLM-5.3 has no comparable published API token rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

API model ID

Gemini 3.5 Flash Cyber

Not sourced

GLM-5.3

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Gemini 3.5 Flash Cyber

No comparable hosted API rate

GLM-5.3

No comparable hosted API rate

Z.AI GLM-5.3 launch post

Documented inputs

Gemini 3.5 Flash Cyber

Not sourced

GLM-5.3

Not sourced

Documented outputs

Gemini 3.5 Flash Cyber

Not sourced

GLM-5.3

Not sourced

Reasoning profile

Gemini 3.5 Flash Cyber

Reasoning

GLM-5.3

Reasoning

Weight access

Gemini 3.5 Flash Cyber

Proprietary

GLM-5.3

Proprietary

License

Gemini 3.5 Flash Cyber

Proprietary

GLM-5.3

Proprietary

Release date

Gemini 3.5 Flash Cyber

2026-07-21

GLM-5.3

2026-08-14

If you already use one of these models
Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
A complete documented context comparison is not available.

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence16 rows

Agentic

  • CyberGym

    Gemini 3.5 Flash Cyber83.2%
    Source
    GLM-5.384.5%
    Source

    GLM-5.3 leads this result

  • Terminal-Bench 2.1

    Gemini 3.5 Flash Cyber—
    GLM-5.388.2%
    Source

    Not directly comparable

  • terminalBench3

    Gemini 3.5 Flash Cyber—
    GLM-5.328.3%
    Source

    Not directly comparable

  • ExploitGym

    Gemini 3.5 Flash Cyber—
    GLM-5.315.0%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Gemini 3.5 Flash Cyber—
    GLM-5.373.0%
    Source

    Not directly comparable

  • AutomationBench

    Gemini 3.5 Flash Cyber—
    GLM-5.348.2%
    Source

    Not directly comparable

  • Agents' Last Exam

    Gemini 3.5 Flash Cyber—
    GLM-5.328.5%
    Source

    Not directly comparable

  • HLE w/ tools

    Gemini 3.5 Flash Cyber—
    GLM-5.362.5%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.1

    Gemini 3.5 Flash Cyber—
    GLM-5.388.2%
    Source

    Not directly comparable

  • terminalBench3

    Gemini 3.5 Flash Cyber—
    GLM-5.328.3%
    Source

    Not directly comparable

  • deepSwe

    Gemini 3.5 Flash Cyber—
    GLM-5.366.9%
    Source

    Not directly comparable

  • NL2Repo

    Gemini 3.5 Flash Cyber—
    GLM-5.358%
    Source

    Not directly comparable

  • ProgramBench

    Gemini 3.5 Flash Cyber—
    GLM-5.319.0%
    Source

    Not directly comparable

  • FrontierSWE

    Gemini 3.5 Flash Cyber—
    GLM-5.378.1%
    Source

    Not directly comparable

  • sweMarathon

    Gemini 3.5 Flash Cyber—
    GLM-5.342.5%
    Source

    Not directly comparable

  • PostTrain Bench

    Gemini 3.5 Flash Cyber—
    GLM-5.339.8%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Gemini 3.5 Flash Cyber or GLM-5.3?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Gemini 3.5 Flash Cyber or GLM-5.3?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Gemini 3.5 Flash Cyber or GLM-5.3?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Gemini 3.5 Flash Cyber or GLM-5.3?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Gemini 3.5 Flash Cyber or GLM-5.3?

A complete documented context-window comparison is not available.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 14, 2026

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