Model A

Google

64.7/100

Estimated · Public rank #39

90% interval 54.1–75.2

Gemini 3.5 Flash vs GLM-5

Updated August 18, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B

GLM-5

Z.AI

65.6/100

Supported · Public rank #33

90% interval 54.5–76.7

Decision reading

GLM-5 has the higher public score estimate, 65.61 versus 64.67, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

9 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.

Long documents
Prompts that approach the documented context limit
Gemini 3.5 Flash
Gemini 3.5 Flash has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
GLM-5
GLM-5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates

Show secondary and unsupported calls

Repository review cost
50K fresh input + 3K output tokens
GLM-5
GLM-5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. GLM-5 does not fit this workload in one request. GLM-5 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback

What is actually comparable

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

14 Gemini 3.5 Flash only

9 Shared

27 GLM-5 only

Shared results: 9
Gemini 3.5 Flash only: 14
GLM-5 only: 27
Like-for-like categories: 0 / 8

4 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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

Directional only

Gemini 3.5 Flash: 77.2
GLM-5: 56.2
Weighted basis: 2 vs 1 rows
Reading: Directional only

Coding

Directional only

Gemini 3.5 Flash: 55.1
GLM-5: 66.3
Weighted basis: 1 vs 3 rows
Reading: Directional only

Knowledge

Directional only

Gemini 3.5 Flash: 40.2
GLM-5: 66.4
Weighted basis: 1 vs 4 rows
Reading: Directional only

Math

Directional only

Gemini 3.5 Flash: 32.9
GLM-5: 56.3
Weighted basis: 2 vs 4 rows
Reading: Directional only

Reasoning

Not comparable

Gemini 3.5 Flash: 74.7
GLM-5: 60.8
Weighted basis: 2 vs 1 rows
Reading: Not comparable

Multilingual

Not comparable

Gemini 3.5 Flash: Not measured
GLM-5: 83.1
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Multimodal

Not comparable

Gemini 3.5 Flash: 83.8
GLM-5: Not measured
Weighted basis: 2 vs 0 rows
Reading: Not comparable

Instruction following

Not comparable

Gemini 3.5 Flash: Not measured
GLM-5: 92.6
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Category averages with the server-provided evidence basis for Gemini 3.5 Flash and GLM-5
Category	Gemini 3.5 Flash	GLM-5	Weighted basis	Reading
Agentic	77.2	56.2	Directional only2 vs 1 rows	Directional only
Coding	55.1	66.3	Directional only1 vs 3 rows	Directional only
Knowledge	40.2	66.4	Directional only1 vs 4 rows	Directional only
Math	32.9	56.3	Directional only2 vs 4 rows	Directional only
Reasoning	74.7	60.8	Not comparable2 vs 1 rows	Not comparable
Multilingual	Not measured	83.1	Not comparable0 vs 1 rows	Not comparable
Multimodal	83.8	Not measured	Not comparable2 vs 0 rows	Not comparable
Instruction following	Not measured	92.6	Not comparable0 vs 1 rows	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.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

FrontierMath v2 (Tiers 1-3)
Math
Gemini 3.5 Flash: 38.966%GLM-5: 16.434%Normalized gap 22.5Shared source
Terminal-Bench 2.0
Agentic
Gemini 3.5 Flash: 76.2%GLM-5: 56.2%Normalized gap 20.0Gemini 3.5 Flash source GLM-5 source
FrontierMath v2 (Tier 4)
Math
Gemini 3.5 Flash: 14.583%GLM-5: 2.100%Normalized gap 12.5Shared source
HLE
Knowledge
Gemini 3.5 Flash: 40.2%GLM-5: 50.4%Normalized gap 10.2Gemini 3.5 Flash source GLM-5 source

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: $0.006; Fits in one request
GLM-5: $0.0026; Fits in one request

GLM-5 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Gemini 3.5 Flash: $0.102; Fits in one request
GLM-5: $0.0596; Fits in one request

GLM-5 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

Gemini 3.5 Flash: $0.15; Fits in one request
GLM-5: $0.252; Does not fit in one request; Cached input priced at the published list-input rate

GLM-5 does not fit this workload in one request. GLM-5 has no published cached-input rate, so cached tokens use its listed input rate.

Specification differences

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

SpecificationGemini 3.5 FlashGLM-5

Context window

Maximum documented context; output-token limits may be lower.

Gemini 3.5 Flash

Google Gemini API pricing

GLM-5

200K

API model ID

Gemini 3.5 Flash

gemini-3.5-flash

Google Gemini API pricing

GLM-5

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

$0.15 per 1M cached input tokens

Google Gemini API pricing

GLM-5

Not published

Documented inputs

Gemini 3.5 Flash

Not sourced

GLM-5

Not sourced

Documented outputs

Gemini 3.5 Flash

Not sourced

GLM-5

Not sourced

Provider availability

Gemini 3.5 Flash

Not sourced

GLM-5

Not sourced

Reasoning profile

Gemini 3.5 Flash

Reasoning

GLM-5

Non-Reasoning

Weight access

Gemini 3.5 Flash

Proprietary

GLM-5

Open Weight

License

Gemini 3.5 Flash

Proprietary

GLM-5

Open Weight

Release date

Gemini 3.5 Flash

2026-05-19

GLM-5

2026-03-01

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: GLM-5 has the higher public score estimate, 65.61 versus 64.67, but the 90% score intervals overlap.
Workload cost: Repository review: $0.102 vs $0.0596. Cache-heavy agent loop: $0.15 vs $0.252.
Context tradeoff: Gemini 3.5 Flash has the larger documented window (1M).

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 evidence50 rows

Agentic

Terminal-Bench 2.0
Gemini 3.5 Flash76.2%
Source
GLM-556.2%
Source
Gemini 3.5 Flash leads this result
MCP Atlas
Gemini 3.5 Flash83.6%
Source
GLM-531.1%
Source
Gemini 3.5 Flash leads this result
Toolathlon
Gemini 3.5 Flash56.5%
Source
GLM-538%
Source
Gemini 3.5 Flash leads this result
OSWorld-Verified
Gemini 3.5 Flash78.4%
Source
GLM-5—
Not directly comparable
Finance Agent v2
Gemini 3.5 Flash57.9%
Source
GLM-5—
Not directly comparable
Gert Labs
Shared source
Gemini 3.5 Flash61.85%
GLM-550.99%
Gemini 3.5 Flash leads this result
ResearchClawBench
Gemini 3.5 Flash18.0%
Source
GLM-5—
Not directly comparable
Claw-Eval
Gemini 3.5 Flash—
GLM-557.7%
Source
Not directly comparable
QwenClawBench
Gemini 3.5 Flash—
GLM-554.1%
Source
Not directly comparable
τ³-bench results
Gemini 3.5 Flash—
GLM-565.6%
Source
Not directly comparable
DeepPlanning
Gemini 3.5 Flash—
GLM-514.6%
Source
Not directly comparable
MCP-Tasks
Gemini 3.5 Flash—
GLM-560.8%
Source
Not directly comparable
WideResearch
Gemini 3.5 Flash—
GLM-569.8%
Source
Not directly comparable
CyberGym
Gemini 3.5 Flash—
GLM-543.2%
Source
Not directly comparable

Coding

Terminal-Bench 2.0
Gemini 3.5 Flash76.2%
Source
GLM-5—
Not directly comparable
SWE-bench Pro
Gemini 3.5 Flash55.1%
Source
GLM-555.1%
Source
Tie
Vibe Code Bench
Gemini 3.5 Flash48.68%
Source
GLM-5—
Not directly comparable
cursorBench31
Gemini 3.5 Flash49.8%
Source
GLM-5—
Not directly comparable
cursorBench32
Gemini 3.5 Flash48.8%
Source
GLM-5—
Not directly comparable
EEBench
Gemini 3.5 Flash34.3%
Source
GLM-5—
Not directly comparable
SWE-bench Verified
Gemini 3.5 Flash—
GLM-577.8%
Source
Not directly comparable
SWE-bench Verified*
Gemini 3.5 Flash—
GLM-572.8%
Source
Not directly comparable
SWE Multilingual
Gemini 3.5 Flash—
GLM-573.3%
Source
Not directly comparable
SWE-Rebench
Gemini 3.5 Flash—
GLM-562.8%
Source
Not directly comparable
React Native Evals
Gemini 3.5 Flash—
GLM-574.8%
Source
Not directly comparable

Reasoning

MRCRv2
Gemini 3.5 Flash77.3%
Source
GLM-5—
Not directly comparable
MRCR 1M
Gemini 3.5 Flash26.6%
Source
GLM-5—
Not directly comparable
ARC-AGI-2
Gemini 3.5 Flash72.1%
Source
GLM-5—
Not directly comparable
LongBench v2
Gemini 3.5 Flash—
GLM-560.8%
Source
Not directly comparable
AI-Needle
Gemini 3.5 Flash—
GLM-563.3%
Source
Not directly comparable

Knowledge

GPQA-D
Gemini 3.5 Flash92.7%
Source
GLM-586.0%
Source
Gemini 3.5 Flash leads this result
HLE
Gemini 3.5 Flash40.2%
Source
GLM-550.4%
Source
GLM-5 leads this result
GPQA
Gemini 3.5 Flash—
GLM-586%
Source
Not directly comparable
SuperGPQA
Gemini 3.5 Flash—
GLM-566.8%
Source
Not directly comparable
MMLU-Pro
Gemini 3.5 Flash—
GLM-585.7%
Source
Not directly comparable
MMLU-Pro (Arcee)
Gemini 3.5 Flash—
GLM-585.8%
Source
Not directly comparable

Math

FrontierMath v2 (Tiers 1-3)
Shared source
Gemini 3.5 Flash38.966%
GLM-516.434%
Gemini 3.5 Flash leads this result
FrontierMath v2 (Tier 4)
Shared source
Gemini 3.5 Flash14.583%
GLM-52.100%
Gemini 3.5 Flash leads this result
AIME26
Gemini 3.5 Flash—
GLM-595.8%
Source
Not directly comparable
AIME25 (Arcee)
Gemini 3.5 Flash—
GLM-593.3%
Source
Not directly comparable
HMMT Feb 2025
Gemini 3.5 Flash—
GLM-597.5%
Source
Not directly comparable
HMMT Nov 2025
Gemini 3.5 Flash—
GLM-596.9%
Source
Not directly comparable
HMMT Feb 2026
Gemini 3.5 Flash—
GLM-586.4%
Source
Not directly comparable
MMAnswerBench
Gemini 3.5 Flash—
GLM-582.5%
Source
Not directly comparable

Multilingual

MMLU-ProX
Gemini 3.5 Flash—
GLM-583.1%
Source
Not directly comparable
NOVA-63
Gemini 3.5 Flash—
GLM-555.1%
Source
Not directly comparable

Multimodal

CharXiv
Gemini 3.5 Flash84.2%
Source
GLM-5—
Not directly comparable
MMMU-Pro
Gemini 3.5 Flash83.6%
Source
GLM-5—
Not directly comparable
Blueprint-Bench 2
Gemini 3.5 Flash33.6%
Source
GLM-5—
Not directly comparable

Instruction following

IFEval
Gemini 3.5 Flash—
GLM-592.6%
Source
Not directly comparable

Frequently asked questions

Which is better, Gemini 3.5 Flash or GLM-5?

GLM-5 has the higher public score estimate, 65.61 versus 64.67, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Gemini 3.5 Flash or GLM-5?

The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Gemini 3.5 Flash or GLM-5?

The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Gemini 3.5 Flash or GLM-5?

For the stated presets, chat costs $0.006 on Gemini 3.5 Flash and $0.0026 on GLM-5; repository review costs $0.102 and $0.0596; the cache-heavy agent loop costs $0.15 and $0.252. GLM-5 does not fit this workload in one request. GLM-5 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Gemini 3.5 Flash or GLM-5?

Gemini 3.5 Flash has the larger documented context window: 1M, compared with 200K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 18, 2026

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Gemini 3.5 Flash vs GLM-5

Which one for your work

Long documents

Chat turn cost

Repository review cost

Coding work

Agentic work

Cache-heavy agent loop cost

What is actually comparable

Category results, on a stated basis

Agentic

Coding

Knowledge

Math

Reasoning

Multilingual

Multimodal

Instruction following

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Benchmark evidence

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Multimodal

Instruction following

Frequently asked questions

Which is better, Gemini 3.5 Flash or GLM-5?

Which is better for coding, Gemini 3.5 Flash or GLM-5?

Which is better for agentic tasks, Gemini 3.5 Flash or GLM-5?

Which costs less, Gemini 3.5 Flash or GLM-5?

Which has the larger context window, Gemini 3.5 Flash or GLM-5?

Related comparisons

Watch Gemini 3.5 Flash vs GLM-5